StudentID: 1
Nickname: a
Q3: B
Honorcode: 2
Date: 1/26/00
Time: 12:00:02 PM
a
b
StudentID: 100962404
Nickname: Sunny
Q3: A
Honorcode: 1
Date: 1/26/00
Time: 3:01:37 PM
Probability is used to determine whether or not to reject the null hypothesis. In general, psychology researchers reject the null if your experiment has a probability of 5% or less. In otherwords, if you were to get a probability of 5% or less, the chances are low that you would have gotten the tested score or result if the null hypothesis were true. However, a low probability does not "prove" the research hypothesis is "true." These words are too strong to be using to conclude your experiment since it is based on probabilities and does not outrule the chance that the null has some chance of being true.
The score at the 95% percentile is 664.5. I found this answer by first finding the z-score, using 95-50, to figure out the percent from the mean to the z-score. I then looked up this number, 45, and found the z-score. Since there were two choices which were both equal distances from 45, I averaged the two z-scores to find a z-score of 1.645. I then plugged this and the givens into the formula, 1.645(100) + 500, which equals 664.5.
StudentID: 101125631
Nickname: Monkeygirl
Q3: B
Honorcode: 1
Date: 1/26/00
Time: 4:23:17 PM
In inferential stats, the concept of probability generalizes the results achieved from a (random) sample, to the rest of the population.
The first step in this problem is 95%-50%=45%. The second step is to find the z score (1.645) via the table in the book. Finally, you have to rearrange the z score formula [to X= (standard deviation)(z score)+mean], and compute to get the value of X (664.5).
The score of 664.5 would be at the 95th percentile.
StudentID: 101780234
Nickname: lucky
Q3: A
Honorcode: 1
Date: 1/26/00
Time: 5:25:07 PM
Probability is the proportion or relative frequency of an event, or how likely a certain event will occur. In hypothesis testing, probability is used to compare two different hypotheses, the null and research hypotheses. If the null hypothesis has an observed probability of less than .05, then we can reject the research hypothesis and accept the null hypothesis. However, if the null hypothesis has an observed probablility of greather than .05, then we can keep the research hypothesis and reject the null hypothesis.
To find the score at the 95th percentile, I first found the z-score for that percentile which is 1.96. (100-95= 5/2= 2.5, 50-2.5= 47.5= % Mean to z= 1.96). Then I did the formula for the raw score x, (x= z*sd + m) So,(1.96*100)+500= 696. The score at the 95th percentile is 696.
StudentID: 100734537
Nickname: cheesecake
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 10:12:32 AM
In testing whether or not to accept the null hypothesis, statisticians use probability. They search for a score that is a RARE occurance assuming that the null hypothesis is true- meaning if the score gotten from experimentation has a probability of occuring less than 5% of the time (p<.05), that score is considered RARE, and the null hypothesis is rejected. In order to find the z score beyond which the probability is less than 5% (or 2.5% when using a two-tailed test) , statistitians look at the area under the normal curve, which is equal to the probability.
The score at the 95th percentile is 664. The percentile is the area under the normal curve that is at or below the score. If the sore is at the 95th percentile, that means that 95% of the area of the normal curve is below that score. To find the score,you must subtract 50 from 95 to determine how much area is between the score and the mean. This results in 45%. Then, by looking at the table, one will find the z score of 1.64 that corresponds to this percentage. Then use the formula for the z score to calculate x: 1.64 x 100 + 500 = 664.
StudentID: 101169420
Nickname: quackers
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 2:15:13 PM
Probability is important b/c it is the way that psychologist go from the results of an experiment to conclusions. Probability is the expected frequency of the an outcome of an experiment. The probability also helps explain how certain that you are about your predictions for an experiment. Last, it aids you in deciding if results from your calculations are rare or common.
X= 664 First, I subtracted 50 from 95 to find the % that 95 was away from 50, which was 45. Thein I used the chart and found the z-score which corresponds to the 45%, which equaled 1.64. Then I plugged the #'s given and the one that i found in to the equation X = (z-score)(SD)+(Mean) and got the answer of X= 664.
StudentID: 100982563
Nickname: Yoda
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 2:21:46 PM
Probability is used in inferential statistics to predict the chance that a certain outcome will occur or the % that the certain outcome did truly occur. You usually look for outcomes in your statistics that are extreme enough to reject the null hypothesis and prove that your research hypothesis is true. To do that one must find results that are far enough beyond the mean in the outlying areas that it lies beyond the % point of 5, or a z score of 1.64. Probability comes into play when you state, from looking at your data, that 95% of the information recieved was in an extreme outlier proving your research hypothesis so that you therefore reject the null. Another way to put, is that you are willing to take a 5% chance in rejecting the null hypothesis. Those points that lie beyond a z score 1.64 are extreme enough for you to take a chance and state that the research is conclusive and the research hypothesis stands. This is how probability plays a role in inferential stats. Probability allows researchers to take their data and make conclusions to create theories. Probaility is the number of successful outcomes vs. the number of total outcomes and you can use the numbers from probability to determine how often an event will occur and if it occurs often enough to have significance.
The 95th percentile is a z test score of 1.65. To find the score you take 1.65 X by the SD(100) and add the mean(500) to get a score of 665. This means that if you scored a 665, you were the same or better than 95% of the people who took the same test, but 5% of those who took the test did better than you.
StudentID: 101337519
Nickname: Trixy
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 2:55:46 PM
In order to test a null hypothesis the concept of probability is used to find out if the results are significant and whether you should accept or reject this hypothesis. To do this the null (hypothesis of no change) and research (hypothesis of change) hypotheses must both be stated. Next it has to be determined at what value a rare occurrence will take place, where the probability is less than .05. Next a z score of the sample must be found making the assumption that the population is normally distributed. After comparing the scores a decision can be made whether or not to reject the null hypothesis. It is rejected when the probablility is less than .05.
A score of 665 would be at the 95th percentile. This was found by first drawing a distribution with the area under the curve equal to 95%. The % that is to the right of the mean was found to be 45% by taking 95-50. Looking up 45% in the chart I found that the z value was 1.65. I next used this value in the formula [x=z(st.dev.) + mean] and found the score to be 665.
StudentID: 101736154
Nickname: mercury
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 2:58:07 PM
PRobability is the proportion or relative frequency of an event. Probability is used in inferential statistics to test whether or not the null hypothesis is true. The probability in any experiment is the area under the curve of a set of data. If the probability of of the outcome is less than or equal to .05, then it is considered a rare outcome. If it is a rare outcome, then the null is rejected and the research hpothesis is accepted. If the probability is greater than .05, then the results are inconclusive.
A z-score of 1.65 would be at the 95th percentile. 95 is 45% from the mean (subract 50 from 95). If you look up 45% in the tables it says that its corresponding zscore is 1.65.
StudentID: 101186427
Nickname: Spunk
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 4:32:00 PM
In almost all psychology reports we draw conclusions by evaluating the probability of getting our research results if theopposite of what we are predicting were true. One can see how probability plays a important role when testing a null hypothesis. When deciding on how extreme a score will have to be to reject the null hypothesis, researchers do not generally use an actual number of units on the direct scale of mearsurement. Instead, they state how extreme a score should be in terms of a probability and the Z score that goes with that probability. The researcher use this probability to decide if they should accept or reject the null hypothesis. In general, pyschology researchers use a cutoff on the comparison ditribution with a probability of 5%that a score will be at least that extreme. Researchers reject the Null hypothesisif the probabilityof getting a result this extremeis less than 5%. If it is greater than 5% the researchers will accept the null hypothesis.
The score that would be at the 95th percentile would be 665. I got this answer by first subtracting 95-50=45. I used the answer 45 and i looked on the z-table chart to see what zscore had a probability of 45. I found that 1.64 had a probability of 44.95 and that 1.65 had a probability of 45.05. Because both of these points were equal distance away from the probability of 45, I decided to use 1.65 as my z- score. I then took 1.65 and i mutiplied it to the standard deviation which was 100. I took this number and added the mean of 500 to it. I came up with the answer 665. What this score of 665 is saying is that if you scored a 665 on an achievement test- then you did better than 95% of the 400 students taking the test. I also checked my answer by comparing it to the mean. The mean is 500 and I know that the mean represents the middle of a normal distribution or 50% of the curve. 95% is a lot more than 50% so i had to come up with a score that quite bigger than 500. This is how I made sure that my answer was right.
StudentID: 101816052
Nickname: chou-chou
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 4:39:27 PM
The concept of probability is used in inferential statistics to serve as a way of determining if there is evidence to prove against the validity of the null hypothesis. For example if a sample of JMU students' GPA's were tested against UVA students' GPA's to see if JMU's were higher, the null hypothesis would be that there were no differences between these two populations. If the JMU scores fell within the top 5 %, or P<= +.05, of the distribution, this would be enough reason to reject the null hypothesis and say tha JMU students have higher GPA's than UVA students. I used a P=.05 because this is a one-tailed test since we only are interested in one end of extremes of the distribution. However, if the JMU students GPA's fell below this mark, there would be no conclusive reason to reject the null hypothesis.
The score would be 664.5. I found this by first determining the percent above the mean that this score would be, (95%-50%=45%). Next I used the z-score chart to find the appropriate z-score for 45%. This I found to be 1.645. I then used the following formula to determine the score, X=SD(z)+mean. X=100(1.645)+500. X=664.5
StudentID: 100710111
Nickname: goose
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 4:43:20 PM
Probability is the "expective relative frequency of a particular outcome." When you test for a null hypothesis, you are looking for a COMMON occurrence defined as having a probablility (area) within 49.95% on each side of the curve. If the score is somewhere out of that range, we call the hypothesis a research hypothesis. This is where scores occur somewhere inside the .05% on either side.
664. I took the 50% I knew to be on the right side of the distribution, and subracted it from 95. This gave me the area under thte curve which was 45. I then looked on the Z tables and found that 1.64 was the Z score for this area. I then plugged my numers into the Z score formula and came up with a score of 664. This by the way is a RARE score.
StudentID: 101954741
Nickname: Angelfire
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 5:20:40 PM
The concept of probability can be used to determine if a score has a rare occurence given the null hypothesis is ture, i.e. determine the cutoff score. A rare occurence is one that occurs with a probability less than .05. Thus, a common occurence is one that occurs with a probability greater .05. From another viewpoint, if the observed Z-score is greater than 1.64, then the event is rare and the null hypothesis is rejected, concluding that the data supports the research hypothesis, and vice versa. The purpose of an inferential statistic, such as hypothesis testing, is to determine whether a particular outcome, such as an observed sample value, could have originated from one of two populations, and this concept is acheivable because of probability.
To answer this question, one must first compute the Z-score for the problem, and because the percent in the problem is 95, one must subtract 95 from 100, which equals 5%, then divide that number in half, then subtract that number from fifty=50%-2.5%=47.5%, and then using the Z-table in the book, looking up 47.5%, one can see that the Z-score is 1.96. Now using the formula X=Z(o) + M, one can compute the x score at the 95th percentile, like so: 1.96(100) + 500=696. And 696 is the answer.
StudentID: 100951026
Nickname: shera
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 5:36:28 PM
Probability is the expected relative frequency of a particular outcome, or the proportion of successful outcomes to all outcomes. The purpose of most psychological research is to prove that something is likely to happen or not at all likely to happen. Research examines the truth of theories, but it cannot tell us that something is 100% true. Probability is very important in inferential statistics because it helps us find out what is most likely to happen. When looking at a graph, probability is equal to the area under the curve. If the curve is divided into two portions, one 50% below the mean, and one 50% above the mean, then if you know the percent that an area covers, you also know a probability. (i.e.- 80% = .8 and 15% = .15) If you know probablitiy, then you can figure out common occurances and rare occurances. By using percentages and probabilities, you can also find z scores which can help you test a null hypothesis.
First of all, someone who scored in the 95th percentile scored better than 95% of the students taking the achievement test. First, I would see that 95% is higher than the mean, so it would be to the right. Then I would realize that only five percent of the students scored higher than this test taker. I would draw a diagram to help me understand and picture the problem, and then I would look in the back of the book to find the (% mean to Z) that is closest to 45, and get a z-score . The z-score that corresponds is 1.645. If I were doing a hypothesis test, this would qualify as a rare occurances because it is greater than 1.64. Next, I would go ahead and find the x score. To do this i would use the equation: zscore(standard dev) + mean. That equals 664.5. So that is the score that corresponds to the 95th percentile.
StudentID: 101115311
Nickname: scoobs
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 5:37:03 PM
Probability is used in inferential statistics as a means of measuring results from research studies. We use probability to determine how sure we are of a particular outcome. In hypothesis testing we determine a cutoff point of how extreme our data must come out in order to reject our null hypothesis. We set this cutoff point through terms of probability. For example we might say that the cutoff is 5% probability. The null hypothesis will be rejected if the result falls into the region less than 5% on the comparison distribution.
A score of 665 would be at the 95th percentile. We determine this because a 95th percentile score correlates to a z-score of approximately 1.65 which can be found by looking up a percentage of 45 in the table(50-5). To get the raw score we use the formula, multiplying the z by the standard deviation and adding the mean: (1.65)(100) + (500)= 665.
StudentID: 101175223
Nickname: rodimus
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 6:00:00 PM
probabililty allows one to relatively interpret the accurateness of one's results, which furthers the strength of the conclusion. testing a null hypothesis is rarely a certain 100% result, probabilities allow us to find out the chances of being right.
665. the 95th percentile is 45% from the mean, which is found in our book as a z score of 1.65. using the equation x=z(standard deviation)+(mean), the answer is 665.
StudentID: 100984765
Nickname: Boomer
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 6:22:56 PM
Probability is "the expected relative frequency of a particular outcome"(p.144). Probablity compares the expected frequency to the actual amount. This idea could be used in inferential statistics through hypothesis testing. The probability represents the area under the curve in a hypothesis test. In these test, a set of data is being studied, and then conclusions are drawn based on these observations. Probablity allows us to look at the possible differences between these two poplulations and compare them to the null hypothesis (that there is no difference). After creating the null and research hypothesis, probability is used to help know what the value will need to be to reject the null hypothesis.
At the 95th percentile, the score would be 513. I derived this answer by first finding the z score using the equation: (X-(Mean))/standard deviation. This value was = -1. Next I sketched a graph of the standard normal curve, and shaded in the 95% area, so that I could see what area I was looking for. Subtracting 95% from 100(total area), I found it was 5%. I then looked up 5% in the Z table, and found that at 5%, the Z score was .13. To find the score at this level, I placed the Z score in the X equation, X(standard deviation) + Mean. This value was the score, 513 at the 95 percentile.
StudentID: 101905648
Nickname: rygy
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 6:23:01 PM
The concept of probability is used in inferential statistics for many reasons. Probability is especially useful in helping psychologists to go from results of research to conclusions about theories or applied procedures. Probablity is also used to test the hypothesis. Whether where are to reject the null hypothesis or fail to reject it.
The score on the test would be 665. You come to this answer by looking up 45% in the table and you find that you can use either 44.95 or 45.05. I chose to use 45.05 which gave me a z score of 1.65. From there I just sustituted the numbers into the formula X=(z)(sd)+ (M), or X=(1.65)(100)+500=665.
StudentID: 101133209
Nickname: Elon
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 6:26:25 PM
The concept of probability is used in inferential statistics in several specific ways, but the underlying use in all of them is the same. They all help psychologists to interpret data and make conclusions. One specific way that probability is used is to determine the expected outcome of an experiment over a period of time. This in a sense tells us what will occur "in the long run." Another specific way that probability is used is to state how certain we are that a particular outcome will occur. This is our confidence interval, or how sure we are.
The score at the 95th percentile is 664.5. I found this answer by finding the z score in the table that corresponds with 45%, which is 1.645. I only looked at 45% and not 95% because the score will be on the right side of the normal distribution, which already implies that it is in addition to 50%. I multiplied that z score by the standard deviation of 100, and then added that number to the mean of 500. The answer is 664.5.
StudentID: 101968018
Nickname: nicholas
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 6:29:45 PM
The concept of probability used in inferential statistics is useful for determining whether a particular outcome, such as an observed sample value, could have originated from one of two populations.
To find this, i applied the formula X = Z score * (std. deviation) + mean in order to find the score (X) at the 95th percentile. The first thing i did was determine was the corresponding Z value is for the 95th percentile. to do this i subtracted 50 from 95, and got a value of .45, and found the corresponding Z value to be 1.645. Then, i plugged this Z value into the original formula to get X = 1.645 * 100 + 500, and got a score of 664.5.
StudentID: 100747476
Nickname: goat
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 6:36:41 PM
Probability is the proportion or relative frequency of an event, ranging from 0 to 1. Its purpose is to determine the likelihood of a particular event occurring so that decisions and/or conclusions can be drawn from that occurrence. An outcome would not be likely if its probability was in the upper-most or lower-most 5% of the probability distribution. Overall, probability is used in inferential stastics to determine if a certain occurrence could have originated from 1 of 2 populations. It allows researchers to go from test results to conclusions about theories or procedures.
The score that would be in the 95th percentile is 664. This score was determined by calculating the value of 'x' in the formula (x-m)/SD=z. Since we are looking for 1 individual score. The z was determined since the 95th percentile would mean that this particular score was higher than 95% of all the scores. The percent, or area under the curve is therefore 45% (above the mean, and 50% below the mean)which can be found in the Z table as having a Z score of 1.64. Therefore, x=664 algebraically.
StudentID: 101974684
Nickname: buttercup
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 6:46:54 PM
Inferential statistics are methods used by psychologists to reach conclusions from results of their research studies. Probability is defined as "the expected relative frequency of a particular outcome." As one can see, both aspects of these statistics contribute in reaching results. Probability helps in describing the results by relating the expected number of times something would happen in relationship to the number of times the researchers expected it to happen. Probability also helps in relating how certain we are that a result will occur. Both of these relate to the idea of the null hypothesis. Psychologists can find out whether or not their research hypothesis, the variable in which they are interested in, can better prove something than the null hypothesis. Psychologists can also use probability when creating research hypotheses to make more accurate assumptions of what hypothesis will be more reliable. It is because of the concept of probability that researchers are able to reach conclusions between both hypotheses.
Since there is a normal distribution, the 95th percentile would fall 45% above the the mean (since the mean is at 50%). In order to find what the score would be at the 95th percentile, one would look up 45% on the z-chart and find the corresponding z-score. The two closest numbers to 45 were 44.95 and 45.05. Since both numbers fall the same distance of .05 away from 45%, either can be used. If using 44.95, one would get a z-score of 1.64. If using 45.05, one would get a z-score of 1.65. The z-score is then used to find x. In order to find x, multiply the z-score by the standard deviation and then add that result to the mean. With a z-score of 1.64, one would get an x of 664. With a z-score of 1.65, one would get an x of 665. Either score, 664 or 665, would be acceptable scores at the 95th percentile.
StudentID: 101220954
Nickname: Nash
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 6:55:19 PM
In science you can never know for certain whether what you are testing is true, you can only know that it is not true. The famous Pythagorus stated that "absence of evidence is not evidence of absence." In inferential statistics, the method psychologists use to go from results of research studies to conclusions about theories or null hypotheses is probability. Probablility is the relative frequency of a particular outcome or experimental result. Any conclusions that we make about a null hypothesis that is being tested must come from the sample statistics, which are taken from a population which cannot be examined in it's entirety, can be compared by probabilities. After comparing the probabilites of two populations, we can either accept or reject our null, or initial hypothesis. If we reject the null hypothesis it means that our probabilities of the population were different in some way that favored the research hypothesis. I we fail to reject the null hypothesis, then our proabilities of the populations were different in some way which favored the null hypothesis. This is how probabilities play a role in inferential statistics.
721 would be the score at the 95th percentile. To get this answer I subtracted 50 from 95 which gave me the percent that the score was above the 50th percentile mark. Then I looked up 45% in the z score table. Given the z score I could determine from the formula x=z(standard deviation)+M, what the rank of the 95th percentile in relation to the other given values including it's deviation from the mean.
StudentID: 101852531
Nickname: Daisy Girl
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 7:02:40 PM
Probablity is the method that Psychologists use to make conclusions about their hypothesis. For example when testing a null hypothesis, if the z-score found is less than a set number, such as 2%, then it is rejected. 2% is a probablity.
The score that would be at the 95th precentile is 696. I got this answer by subtracting 95 from 100 and then dividing the answer by 100 - this is the confidence level. Next, you find the z score of 0.05, which is 1.96. Using the formula x=z(SD)+M, the score is 696.
StudentID: 101194842
Nickname: moggy
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 7:33:12 PM
The concept of probability is used in inferential statistics to psychologists because it is the method they use in translating results of research into their conclusions about theories and procedures. The concept of probability used in testing a null hypothesis is when there is no difference between the two probabilties. This is the opposite of the research hypothesis.
665 would be the score at the 95th percentile. To find this answer you would first find the % Mean to Z by subtracting 50 from 95. The answer you get is 45 and then using this number you look up the z-score using the table in the book. After you find the z-score you solve for X using the formula X=Z(standard deviation)+the mean. This gives you your final answer of 665.
StudentID: 101926641
Nickname: Shakaspara
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 7:56:26 PM
When testing a null hypothesis, a critical value is used to determine whether or not the results of a hypothesis test are significant, or valid, or not. If after performing a hypothesis test, the value gotten is below or above the critical value, it is probable that the null hypothesis is not true.
X=664 I obtained this answer by first drawing a graph of a normal distribution and marking the mean at 500, and three standard deviations from the mean. I drew and shaded an estimate of 95% of the area under the curve. Then I subtracted 50% from 95%, because I am only interested in the area to the right of the mean. I came up with 45%, which is the area that we are interested in. Checking the table on page 564, I determined that the z score for 45% is 1.64. I used the formula for obtaining a z score, simply putting an X in place of the individual score, so that the equation I worked looked like this: (X-500)/100=1.64 I multiplied the z score by 100, then added 500 to solve for X, coming up with the answer of 664.
StudentID: 100959428
Nickname: butterfly
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 8:36:22 PM
The concept of probablitity is used in statistics to go from results of research studies to conclusions about theories or applied procedures.
A score of 665 would be at the 95th percentile. I dervived my answer by first drawing the curve and marking where 92% would fall and then subtracting 50 from it and getting 45%. I then looked up 45 under the % mean to z and found the corresponding z score, which was 1.65. I then multiplied the z score (1.65) by the standdard deviation (100) and added that to the mean (500) and I got a score of 665. I then checked my answer by marking on the curve where 665 would be and saw if it was at the 95th percentile.
StudentID: 100936160
Nickname: sketchy
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 8:39:13 PM
Probability is "the proportion or relative frequency of an event." Rare outcomes occur if the probability is less than .05. In testing a null hypothesis, it is rejected if the area is less than .05 and accepted if the area is greater than .05.
664.5 would be the score at the 95th percentile. I began by drawing a normal distribution curve, marking the mean and an estimated point for the 95th percentile. Then I subtracted 50 from 95 because I needed the percentage of the normal curve between the mean and the 95th percentile. This gave me 45 percent. Then I looked up the corresponding Z score for 45, which was not listed in the chart. I then had to use the closest percentage, which could have been 44.95 or 45.05; I chose to use 44.95, with a corresponding Z score of 1.64. To find the score at the 95th percentile, I used the formula x = Z(SD)+M = 1.64(100)+500 = 664.5.
StudentID: 100996799
Nickname: tank
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 8:44:09 PM
Probability is very important in inferential statistics, the methods psychologists use to go from results of research studies to conclusions about theories or applied procedures. Also probabilities are used to see where the results stands in then null hypothesis testing, just like the z scores.
I would take 500-400 divide it by 100 and get my answer. It would be 100 over 100 and it equals .1 and that's how I would derive my answer.
StudentID: 101385622
Nickname: Kit Kat
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 9:14:59 PM
When testing a null hypothesis, the experimenter must make sure the results from the sample can be generalized to the population as a whole. They must be 95% sure that, under the same conditions, the same results would be achieved with a different sample.
I subtracted 50 from 95 and found that 1.65 is the z score that is 45% from the mean. I then multiplied 1.65 by 100 (the standard deviation) and added 500 (the mean). I found that the score of 665 would be at the 95th percentile.
StudentID: 101566449
Nickname: Peaches
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 9:24:48 PM
When we test a null hypothesis, the concept of probability is useful to indicate the chance that there is no difference between two populations. We us the concept of probability to get a Z-score. We then find what Z-score the sample must have on the comparison distribution to reject the null hypothesis.
Because I am an aspiring psychology student I know that 1.645 gives me a 95th percentile which is a great thing because it means I can reject the null hypothesis and conclude the my research hypothesis holds validity. But this is how I would calculate it had I not had it memorized.... 95-50= 45 Then I look up 45% on the z-table chart and that gives me 1.65.
StudentID: 101274025
Nickname: SA
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 9:50:15 PM
In inferential statistics probability is equal to the area under the curve, or the percentage. When testing a null hypothesis, you need to calculate the probability or percentage rate in order to deterimine if what you are testing is a rare occurence or considered to be normal. In inferential statistics, if the data has a probability of less than 0.05, then it is deamed to be rare and you would reject the null hypothesis and support the research hypothesis. You must find out the probability in order to know which hypothesis to reject or accept.
The score at the 95%tile would either be 664 or 665. I derived this answer first by realizing that saying 95%tile was equal to 0.05 probability. As I learned in class, 0.05 probability is equal to a z-score of 1.64. From there, I used the equation x=z(standard deviation) + the mean. Using the z-score of 1.64 and the standard deviation of 100 and mean of 500, the score that I derived is 664.
StudentID: 101967921
Nickname: Betty Boop
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 9:53:34 PM
The concept of probability is used in inferential statistics in a few ways. First, the area shaded in, or the area under the curve, reprsents the probability that an event will happen. Probability also determines if an outcome is rare or common. If the Pr(outcome)<.05, then it is a rare outcome. Otherwise, it is a common outcome. Usually with testing a null hypothesis, you would only reject the null, and accept the research hypothesis, if the probablitiy of is less than .05. If is over .05, it would be considered inconclusive and you would fail to reject the null hypothesis.
x=665 To get this answer I subratected 50 from 95, then looked up that answer (45) on the table. Using the formula: x=z (sd) + m, I got x=1.65 (100) + 500 = 665. I drew a graph to make sure my answer seemed reasonable, and it did.
StudentID: 100632956
Nickname: froggy
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 10:00:52 PM
In inferential statistics hypothesis testing is used to determine whether an outcome could have come from 1 of 2 populations. One has to find out how likely an event is to happen to see if one should accept or reject the null hypothesis. When once tested, a probablity of .05 or less means that the null hypothesis is rejected, because the probablity shows a rare occurance and the null hypothesis is a common occurance.
A score at the 95th percentile is equal to a percentage of 45 above the mean. When looking at the table of the normal curve areas, 45% is equivalent to a z-score of 1.64. One must take this information and plug it into the formula to find the raw score, X. X= (1.64*100)+500
X=664
StudentID: 101176381
Nickname: scooter
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 10:53:11 PM
A probability is the % chance that an event will occur. In testing a null hypothesis, the probability is very important. If the probability of an event occuring is less than or equal to .05 (i.e. z > 1.64 or z < -1.64), than you would conclude that the event is rare and decide to reject the null hypothesis and conclude that the data support the research hypothesis. In other words, the probability is used to make conclusions about the data.
The score at the 95th percentile will be 608 or better. I found the z score by looking up 45% in the tables (95-50, which gives me the area between the 95th percentile and the mean) and I got 1.08. I the took the z score and multiplied by 100 (the standard deviation) and added 500 (the mean). I received a score of 608, which is the score at the 95th percentile.
StudentID: 101099628
Nickname: smurf
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 10:54:36 PM
The purpose of most psycological research is to examine the truth of a theory or the effectiveness of a procedure. This only lets us know whether something is more or less likely to happen, we don't know for certain. Probability is used in inferential statistics to measure the chances that a certain event will occur.
Since the z-table only gives scores to the left of the mean 95% is not in the table, therefore, I substracted 50% from 95% and got 45% which is listed in the z-table. Once I got this percentage I found the z-score which was 1.64. I could then find the score that would be in the 95th percentile by using this formula: X=(z)(SD)+M Z=1.64, SD=100, M=500. The score that would be in the 95th percentile is 664.
StudentID: 101921521
Nickname: Sweets
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 11:10:10 PM
In particular, probability is very important in inferential statistics, the methods psychologists use to go from results of research studies to conclusions about theories or applied procedures. In the example of a null hypothesis or hypothesis testing in general, we have to examine the probability that the result of a study could have come about even if the actual situation was that the experimental procedure made no difference. If this probability is low, the scenario of no difference is rejected, and the theory from which the experimental procedure was proposed is supported.
n = 400 mean = 500 sd = 100 The 95th percentile is 45% above the mean. (95-50 = 45) Look on the tables located in the textbook, in the column labeled % MEAN TO Z. Look for the number 45. When you find it, the z-score that goes with it is 1.64. Then, use the formula, X = z(SD)+ Mean. (1.64)(100) + 500 = 664. The X score that would be at the 95th percentile is 664.
StudentID: 100986806
Nickname: Suzy-Q
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 11:16:31 PM
The concept of probability tells us the proportion of successful outcomes to all outcomes. It also tells us the expected relative frequency of a specific outcome. In terms of the null hypothesis, probability can tell us how certain we are that a particular thing will happen. This can convey how probable it will be that we either will accept or reject the null hypothesis.
The score at the 95th percentile would be 665. I derived this answer by completing a Z-Test. First I subtracted 50 from 95 which left me with 45. The Z score for 45% is 1.65. Then I plugged that number into the equation Z=X(SD)+M which was X=1.65(100)+500. This gave me the answer of 665.
StudentID: 100896105
Nickname: honeydo
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 11:17:33 PM
Inferential statistics uses probabily as a means to expand on the data that are collected. If psychologists (or any other person) relied soley upon data that was collected then no one could assume anyTHING beyond that of the tested data of those subjects. This is where probability becomes imortant. A study can not prove that a hypothesis is true. Instead, studies are designed to show that a hypothesis (such as the null hypothesis) can not be rejected. For a study to be proven statistically significant, the probability must be greater than 5%. An outcome is considered rare if the probability of the outcome is less than or equal to 5%.
x=664.5
To derive this answer, I drew a normal distribution curve and because the 95% was to the right of the mean, I subtracted 50 from 95. This informed me that 45% was to the right of the mean. In the z table, i found that for the 45%, z was equal to 1.645 (z was exactly half was between 1.64 and 1.65). Since [x= z (standard deviation) + mean] I plugged in the numbers. x= 1.645 (100)+500 = 664.5
This answer makes sense because z=1 would be 600 and z=2 would be 700 therefore meaning z=1.645 should be between those.
StudentID: 100508589
Nickname: squid41
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 11:26:06 PM
The concept of probabilty in statistics can be found when using Confidence intervals. How su do yo want to be about something a standard confidence interval would be 95% or .05 level of signifigance
N=400 M=500 SD=100 95th percentile, .95 has a Z score of 1.65, then we need to find the corresponding test core with a Z score of 1.65 using formula X=Z(sd)+M we find that the corresponding test score would be 665
StudentID: 100879061
Nickname: brianimal
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 11:28:06 PM
The concept of probability is used in inferential statistics to help determine the characteristics of the comparison distribution (assuming the null hypothesis is true). Since the probability is the area, it can be used to help determine if a score has a rare occurance. In order to be a rare occurance, the probability has to be greater than .05. This is also used to determine whether or not to accept or reject the null hypothesis.
The score of 665 would be in the 95th percentile. To come to this answer, you first subtract 50 from 95, which is 45, to account for 50% of the graph. The next step is to find the z score by looking under the area of 45 in the table. The closest number in the table is 45.05 and the correspond z score is 1.65. The next step is to multiply the z score and the standard deviation and then add that number to the mean, which gives you a score of 665.The
StudentID: 101244082
Nickname: applebum
Q3: B
Honorcode: 1
Date: 1/27/00
Time: 11:49:34 PM
The concept of probablity is used in inferential stats by utilizing numbers to represent data that can be later used to describe larger populations or results that can be applied to the general sample.
I would first draw the diagram of the normal distribution and put the mean, 500, in the middle of the graph. Then I would mark the 95th percentile, seeing that 50% is to the left of the mean, and 45% is to the right. We are solving for the raw score that is at the 45%. I then found the Z-score of 45% from the mean, and it was 2.22 I then used the formula for finding X and plugged in all the other variables that were given in the problem previously. After all that, I found the X score to be equal to a score of 722 on the achievement test.
StudentID: 101264596
Nickname: Droopy
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 11:51:06 PM
Probability is used in statistics to test whether or not a null hypothesis can be rejected or not. If the probability is less than .05 then the null hypothesis is rejected and you can say the alternative hypothesis is probably true.
665, the score is 45% above the mean; that makes the z score 1.65, plug the numbers into the formula z(s) + the mean and it equals 665
StudentID: 101847140
Nickname: tigerlily
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 11:51:47 PM
Probability is the expected relative frequency of a particular outcome. Inferential statistics are described as procedures for drawing conclusions based on the scores collected in a research study, but going beyond them. The null hypothesis can be described as a contrived statement set up to examine whether it can be rejected as part of the hypothesis-testing process. Each of these concepts, using key words such as "expected outcomes", "drawn conclusions", and "contrived statements", are linked to one another by all being educated guesses. This is how each concept is used in relation to the other.
Given: mu = 500 sd = 100
1.) Calculate the Z score: z = 95-50 = 45 (this is the % Mean to Z) * Look up 44.95 because it is closest to 45 on Appendix B Table * 44.95 has a Z score of 1.64 * therefore z = 1.64
2.) Solve for x: x = z(sd) + mu x = 1.64(100) + 500 x = 664
If 400 students took an achievement test, with the mean being 500 and the standard deviation being 100, the score that would be at the 95th percentile is equal to 664.
StudentID: 101229881
Nickname: Artee
Q3: A
Honorcode: 1
Date: 1/27/00
Time: 11:52:47 PM
Probablility is the proportion of relative frequency of an event, therefore it is used in inferential statistics. Testing the probablility can determine whether a null hypothesis will be rejected or accepted. If the probablility is less than .05 then the null hypothesis is rejected, if it is greater than .05 then it will be accepted.
The variable we are trying to determine is X which equals score. We will use an equation which equals, z-score times standard deviation plus the mean, to get X. To start this problem you must first draw a normal curve and determine the area under the curve that you have been given. In this example it is 95%. The next step is to calculate the z-score. To do this, you must subtract 95 from 50, because one half of the normal curve equals 50. From this you get -45.Then you use this number to find the z-score by looking on a chart in the textbook. The z-score for this percentile is 1.65.Then we plug in all the numbers we have been given into the equation to find X. The score comes out to be 665.
StudentID: 101983655
Nickname: beanpole
Q3: A
Honorcode: 1
Date: 1/28/00
Time: 12:23:12 AM
Probability is very important to inferential statistics, The methods psychologists use to go from results of research studies to conclusions about theories or applied procedures. Probability is the proportion or relative frequency of an event. Rare outcomes occur if probability of an outcome is less than .05 (z greater than 1.96 or less than -1.96). Using this information we then determine if our results have a rare occurrence given the null hypothesis is true. Once you determine your z score and compute the results, assuming the distribution is a normal one, you can determine whether to accept or reject the null hypothesis. If the probability is less than .05 then you reject, if the probability is more than .05 then you accept.
The score at the 95th percentile would equal 664. I derived my answer by using the formula [x=z(standard deviation)+ Mean]. First I figured that in a normal distribution 95 is 45% above the Mean. This is so because the right of the mean is composed of 50% so (50+45=95). Then I looked up 45% in the table located in the back of our textbook and found that the z-score was 1.64. After all of these enjoyable steps were finished I then plugged my numbers into the formula and computed my answer. [x=1.64(100)+500] Therefore x=664.
StudentID: 101945293
Nickname: rynoshaft
Q3: B
Honorcode: 1
Date: 1/28/00
Time: 12:44:07 AM
Probability is used to exemplify a predicted rate (frequency) of an outcome. A high probability indicates that the result is expected to occur with a high frequency, much as a low probability indicates the expectation of a low frequency. The use of probability is key to inferential statistics because inferential statistics are not absolute (because inferential statistics do not test every possible subject, rather, they test a sample and infer as to results of the whole population). Since inferential statistics seek to apply the data beyond the test subjects, there is no way for them to be 100% absolutely conclusive. For this reason, we must state how likely something is to occur with a probability. Probabilties run from 0-1 (representing 0%-100%). [One must be careful not to apply 100% probabilities, because one can never know if there's an exception to the rule without testing all possible subjects]. In most fields of statistics, a probability of 95% is considered to be highly accurate (or approximately within 2 standard deviations of the mean). While the high probability means that it is 95% likely that the hypothesis will hold true, there is a 5% probability that it will not occur (and thus the null hypothesis will hold true).
SD = 100 mean = 500 x= 400 using the chart on page 564, one finds that z = 1.65 next we reconfigure the following formula: z = x - mean/sd
into: (1.65 * sd) = x - mean
by cross-multiplying, then we solve for x: x = (1.65 * sd) +mean = (1.65 * 100) + 500 = 165 + 500 = 665
x = 665
StudentID: 101137818
Nickname: giggle box
Q3: B
Honorcode: 1
Date: 1/28/00
Time: 12:47:28 AM
The null hypothesis is used to indicate a situation in which there is no difference between two populations. By knowing the probability of something occurring, we then have a better idea of what to expect as our outcome.
M=500, SD=100 X=Z(SD)+M 95-50=45, then I looked 45 up on the z score table and found that it was equivalent to 1.65. X=1.65(100)+500 X=665
StudentID: 101142423
Nickname: mighty mouse
Q3: B
Honorcode: 1
Date: 1/28/00
Time: 12:56:21 AM
Probability is the area under the curve. It helps you to find if there are rare outcomes that would cause you to either accept or reject the null hypothesis. You also have to use probability to determine what the cutoff score is.
The score that would be at the 95th percentile would be 455. You take the percentile number and subtract it from 50. Then you divide that answer by 100, which is the standard deviation. Then you take the number that you got and put it into the formula that consists of the decimal number times or multiplied by the standard deviation plus the number that equals mu.
StudentID: 100652169
Nickname: monkeydoodle
Q3: B
Honorcode: 1
Date: 1/28/00
Time: 1:00:33 AM
The concept of probability is used in inferential statistics to show how extreme a score will need to be in order to reject the null hypothesis. The point at which the null hypothesis is rejected is called the cut-off point. Generally, psychological researchers will use a cut-off with a probability of 5%, also written as p<.05. This states that the psychological researcher will reject the null hypothesis if getting such an extreme score will have a probability of less than 5 percent.
A score of 665 would be at the 95th percentile. I derived this answer by first subtracting 50% from 95%, giving me 45%. I then loked up the z-score of 45% to find the relative location of the score, which was 1.65 standard deviations above the mean. I then took the z-score and multiplied it by the standard deviation of 100 (given in the problem). I then added this figure to the mean of 500 and got the answer of 665, the score that would be found at the 95th percentile.
StudentID: 101835826
Nickname: Lightning Bolt
Q3: A
Honorcode: 1
Date: 1/28/00
Time: 1:06:17 AM
Basically, probabilities involving samples and populations are the foundation of inferential statistics. When doing an experiment between two variables, you find out the result. You then need to find the probability of the samples being the same or different. If the probability is low, then you would reject the hypothesis that there is no difference. This leads to how we find the conclusion to experiments and the statistics we make out of them.
First I subtracted the %: 95-50=45 That is the % I looked up to find the z-score which was 1.65 I then used this formula: x= z (SD)+ M (1.65)(100)+(500)= 665
StudentID: 101278100
Nickname: skibum
Q3: B
Honorcode: 1
Date: 1/28/00
Time: 1:09:13 AM
The concept of probability used in inferential statistics is used to test the outcomes and allow for a deeper understanding of what a group of statistics has to offer in the way of information. It can also determine if an outcome of an abserved sample value could have originated from one of the populations. It allows the experimenter to see if what he is looking at is rare or common dependant upon the outcome of the z-score. If the outcome of the statistic he is testing is smaller or larger than .05 he knows that the statistic is rare. This will let him make a decison about the group that he is testing.
i believe that the answer would be that to recieve a score at the 95% you would have to get a 665. The reason that i say that the score would have to be 665. Is that at the 95th% the z-score that corresponds with that is 1.65. The formula to get the z-score is x-m/sigma. If you were to plug in the numbers into the formula it looks like 1.65= (answer)-500/100. when you do the algebra fot this problem you get the answer that satisfies that problem is 665. which corresponds with the 95th %.
StudentID: 100689400
Nickname: Chip Douglas
Q3: A
Honorcode: 1
Date: 1/28/00
Time: 1:31:57 AM
Probability is the expected relative frequency of a particular outcome. It is calculated as the number of successful outcomes divided by the number of all possible outcomes. When testing a null hypothesis, probability is used to determine how extreme a score will have to be to reject the null hypothesis. This score would have to be too unlikely to get if the null hypothesis were true. It is known as a cutoff sample score.
First, I drew the normal curve and shaded in the top 5 percent. I then found the z score by determining the percent between the mean and the 95th percentile. Since 50 percent of the students had test scores above the mean, 45 percent had test scores between the mean and the 95th percentile. From the "%mean to Z " column of the normal curve table, the closest score to 45 percent was 44.95 percent. This corresponded with a z score of 1.64. Lastly, I calculated the raw score using the formula, X=(Z)(SD)+M. The score at the 95th percentile was 664 (X=(1.64)(100)+500)).
StudentID: 100881989
Nickname: scrubski
Q3: A
Honorcode: 1
Date: 1/28/00
Time: 2:12:39 AM
If the probability is greater then .05 then the null hypothesis is true. If it is less then or equal to .05 then the null hypothesis is false(this is the desirable outcome).
The score would be 664. I know this because I am a genius. KIDDING. It is simple, all you need to do is plug in some scores into the formula, score= (zscore)(SD)+ mean The z-score is obtained using the table in the book.
StudentID: 101105091
Nickname: sly
Q3: A
Honorcode: 1
Date: 1/28/00
Time: 2:22:28 AM
Probability is the area under the curve, and is very useful to inferential statistics. When the outcome observed has a probability greater than .05, then the outcome is considered rare and you must reject the null hypothesis and conclude that the data supports the research hypothesis. However, if the outcome's probability is less than .05, then the event is considered common and the data is inconclusive.
The score at the 95 percentile would be 665. To determine this you must subtract 50 from 95 to get the answer of 45. Then you look up the z-score which is 1.64. You then use the formula x=(z)(SD)+M and put in the numbers x=(1.64)(100)+500 and get the answer that x=665, which is the score at the 95 percentile.
StudentID: 100833872
Nickname: hairball
Q3: B
Honorcode: 1
Date: 1/28/00
Time: 9:49:49 AM
Probability is used to determine how extreme a score has to be in order to reject the null hypothesis. A Z score will go with the probability. A one percent cutoff is used if researchers want to be especially cautious. A sample score that is so extreme that researchers reject the null hypothesis is statistically significant.
95-50=45 Z=1.64 x=1.64 X 100 + 500 =664 The percent mean to Z is found and from there you find the Z score. The Z score is multiplied by the standard deviation and added to the mean giving the score at the 95th percentile.