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Statistics The Exploration And Analysis Of Data 007th Edition Roxy Peck, Ay L Devore - Solutions
14. In the SPSS output, if p = 0.000, then you should report this as:(a) = 0.000(b) = 0.0001(c) 60.001(d) 60.0001
13. In an analysis using an unrelated t-test, you find the following result:Levene’s Test for Equality of Variances: F = 0.15, p = 0.58 This shows that the variances of the two groups are:(a) Dissimilar(b) Similar(c) Exactly the same(d) Indeterminate
12. If the 95% confidence limits around the mean difference (in a t-test) are 10.5 - 13.0, we can conclude that, if we repeat the study 100 times, then:(a) Our results will be statistically significant 5 times(b) Our results will be statistically significant 95 times(c) 95% of the time, the
11. The effect size for independent groups,d, can be calculated by:(a) (mean 1 - mean 2) , mean SD(b) (mean 1 + mean 2) , mean SD(c) (mean 1 - mean 2) , SEM(d) (mean 1 + mean 2) , SEM
10. What can you conclude from the results?(a) There are no statistically significant differences or important differences between the two groups(b) There is a statistically significant difference but it is not important(c) There is an important difference between the two groups but it is not
9. The variances of the two groups are:(a) Indeterminate(b) Unequal(c) Assumed to be equal(d) Skewed
8. The difference between the means of the groups is (correct to one decimal place):(a) 0.41(b) 0.69(c) 0.96(d) 0.76
7. A t-value of -5 is:(a) Less important than a value of +5(b) More important than a value of +5(c) Equivalent to a value of +5(d) Less significant than a value of +5
6. The higher the t-value, the more likely it is that the differences between groups are:(a) A result of sampling error(b) Not a result of sampling error(c) Similar to each other(d) None of the above
5. The most important assumption to meet when using a t-test is:(a) The variation in scores should be minimal(b) Scores should be drawn from a normally distributed population(c) Conditions should have equal means(d) All of the above
4. One hundred students were tested on their anxiety before and after an anxiety counselling session.Scores are drawn from a normally distributed population. Which statistical test is the most appropriate?(a) Independent groups t-test(b) Related measures t-test(c) Levene’s test(d) None of these
3. For an independent t-test with 15 participants in each condition, the appropriate DF is:(a) 28(b) 14(c) 30(d) 15
2. For a paired t-test with 40 participants, the appropriate DF is:(a) 20(b) 39(c) 38(d) None of these
1. The DF for an independent t-test analysis with 20 participants in each condition is:(a) 38(b) 20(c) 40(d) 68
3. Look at the table above.(a) Which result was the one which didn’t show improvement between pre- and post-diagnosis?(b) Which pair showed the strongest effect size between pre- and post-diagnosis?
2. The difference between the mean of condition 1 and 2 is:(a) 8.3(b) 7.558(c) 2.390
1. The value of the test statistic is:(a) 0.007(b) 8.30(c) 3.47
6. t is easy to become confused sometimes when psychologists use several different names for the same thing. What are the alternative names for within-participants designs? What are the alternative names for between-participants designs?
5. What does the independent t-test examine?(a) The difference between the median values for each condition(b) The differences between the variances for each condition(c) The differences between the mean scores for each condition?
4. Inferential tests – t-tests discover how likely it is that the difference between the conditions could be attributable to sampling error, assuming the null hypothesis to be true.
3. Confidence limits around the difference between the means.
2. Effect size – this is a measure of the degree to which differences in a dependent variable are attributed to the independent variable.
1. Descriptive statistics, such as means or medians, and standard deviations; confidence intervals around the mean of both groups separately, where this is appropriate; graphical illustrations such as box and whisker plots and error bars.
■ confidence intervals (Chapter 4)
■ statistical significance (Chapter 5)
■ one- and two-tailed hypotheses (Chapter 5)
■ probability distributions like the t-distribution (Chapter 5)
■ assumptions underlying the use of parametric tests (Chapter 5)
■ z-scores and the normal distribution (Chapter 4)
20. If you find in a study that your p-value is 0.05, what is the probability of the alternative hypothesis being true?(a) 0.05(b) 1 minus 0.05(c) We cannot work out the probability of the alternative hypothesis being true(d) None of the above
19. Imagine we conduct two studies. In study A we have 1000 participants and obtain a p-value of 0.01, whereas in study B we have only 20 participants and a p-value of 0.05. In which of these two studies is there the larger effect?(a) Study A(b) Study B(c) The effect is the same in each study(d) We
18. When we convert our data into a score from a probability distribution, what do we call the value we obtain?(a) Significant(b) Not significant(c) The test statistic(d) The power of the study
17. Why do we usually set our criterion for significance at 0.05?(a) This is the traditional level used by most psychologists(b) This represents a good balance between making Type I and Type II errors(c) It is easier to get significant results with this α(d) Both (a) and (b) above
16. How do we denote power?(a) α(b) β(c) 1 - α(d) 1 - β
14 seconds. Which of the following statements is true?(a) She should not use parametric tests because she has failed to meet the assumption of homogeneity of variance(b) She has completely met all of the assumptions underlying the use of parametric tests(c) She has failed to meet the assumption of
15. A researcher has conducted a study on reaction times with 20 participants in each of two conditions.She finds that the variance for the first condition is 2 seconds and for the second condition is
14. A Type II error means:(a) We have rejected the null hypothesis when it is, in fact, true(b) We have accepted the experimental hypothesis when it is false(c) We have accepted the null hypothesis when it is, in fact, false(d) None of the above
13. Which of the following are the assumptions underlying the use of parametric tests?(a) The data should be normally distributed(b) The samples being tested should have approximately equal variances(c) You should have no extreme scores(d) All of the above
12. If we reject the null hypothesis when it is, in fact, true then we have:(a) Made a Type I error(b) Made a Type II error(c) Made scientific progress(d) Both (b) and (c) above
11. If you predict that there will be a difference between condition A and condition B, what is the null hypothesis?(a) That condition A will be greater than condition B(b) That condition B will be greater than condition A(c) That condition A will be related to condition B(d) That there will be no
10. If you obtain a p-value of 4%, what does this mean?(a) The probability that the null hypothesis is true is 4%(b) The probability that the null hypothesis is false is 4%(c) The probability of obtaining the effect you have due to sampling error if the null hypothesis were true is 4%(d) All of the
9. If we predict that there will be a difference between condition A and condition B, we have made:(a) A one-tailed prediction(b) A two-tailed prediction(c) A null prediction(d) Both (b) and (c) above
8. If you obtain a two-tailed p-value of 0.02, the equivalent one-tailed p-value would be:(a) 0.01(b) 0.04(c) 0.02(d) 0.4
7. The probability that an effect has arisen due to sampling error given that the null hypothesis is true is denoted as:(a) Negligible(b) β(c) α(d) None of the above
6. When we predict that condition A will be greater than condition B, we have made:(a) A one-tailed prediction(b) A two-tailed prediction(c) A uni-directional prediction(d) Both (a) and (c) above
5. The power of an experiment is:(a) α(b) The ability of the experiment to reject the null hypothesis if it is, in fact, false(c) The sensitivity of participants to your experimental manipulation(d) All of the above
4. If you predict that two variables A and B will be related, what is the null hypothesis?(a) That there is no relationship between A and B(b) That A will be greater than B(c) That there is no difference between A and B(d) None of the above
3. If you obtain a one-tailed p-value of 0.02, the equivalent two-tailed p-value is:(a) 0.01(b) 0.04(c) 0.02(d) 0.4
2. What is the basis or logic of inferential statistical tests?(a) To work out the probability of obtaining an effect due to sampling error when the null hypothesis is true(b) To work out the probability of obtaining an effect due to sampling error when the null hypothesis is false(c) To work out
1. A Type II error occurs when:(a) The null hypothesis is not rejected when it should be(b) The null hypothesis is rejected when it should be(c) The null hypothesis is rejected when it should not have been(d) The null hypothesis is not rejected when it should not have been?
95% confidence intervals.6. Convert the first score from each condition into a z-score.1. Is this a between-participants or a within-participants design?2. What sort of variable has Dr Pedantic measured: categorical, discrete or continuous?(a) What is the IV?(b) What is the DV?3. Is the prediction
the standard error
the standard deviation
the mean
error bar charts
What it means to make directional (one-tailed)and non-directional (two-tailed) predictions and how these are related to probability distributions.1. Is this a between-participants or a within-participants design?2. What sort of variable has Professor Yob measured: discrete or continuous?(a) What is
Type I errors are when you reject the null hypothesis when it is, in fact, true.– Type II errors are when you fail to reject the null hypothesis when it is false.
In hypothesis testing there are two general sorts of errors (Type I and Type II errors) that you could make when drawing conclusions from your analyses:
As a result of this we have suggested several ways of supplementing the results of your hypothesis testing with more meaningful statistics, for example effects sizes and confidence intervals.
Although hypothesis testing is the major research method in psychology there is growing concern over its inability to establish meaningful conclusions from our data.
How we can use probability distributions to work out the probability that the effects in our research are due to sampling error if the null hypothesis were true.
The null hypothesis represents no effect and as such represents the converse of the experimental hypothesis.
The logic behind hypothesis testing and statistical significance.
Where statistical tests do not make assumptions about the underlying distributions or estimate the particular population parameters, these are called non-parametric or distribution-free tests.
Many statistical tests are based upon the estimation of certain parameters relating to the underlying populations in which we are interested. These sorts of test are called parametric tests. These tests make assumptions that our samples are similar to underlying probability distributions such as
Many statistical tests that we use require that our data have certain characteristics. These characteristics are called assumptions.
(g) It is predicted that as anxiety increases the number of units of alcohol drank per week will also increase?
(f) It is predicted that there will be a difference between middle-class parents and working-class parents in their preferences for children wearing school uniforms
(e) It is predicted that there will be a relationship between the number of books read per week and range of vocabulary
(d) It is predicted that football fans will have lower IQ scores than opera fans
(c) It is predicted that there will be a relationship between length of hair in males and number of criminal offences committed
(b) It is predicted that, as annual salary increases, so will the number of tomatoes eaten per week
(a) It is predicted that females will have higher empathy scores than males
Which of the following are one-tailed hypotheses and which are two-tailed?
(c) You find in a study that there is a relationship between standard of living and annual income. However, because the probability associated with the relationship is 0.5, you conclude that there is no relationship between standard of living and annual income.
(b) You find in a study that there is no difference between the speed at which cheetahs and tortoises run. You conclude that tortoises are as fast as cheetahs
(a) You find in your study that a relationship exists between amount of tea drunk per day and amount of money won on the Lottery. You conclude that to win the Lottery you need to drink lots of cups of tea
Which of the following represent Type I and which represent Type II errors?
A Type II error is where you conclude that there is no effect in the population when in reality there is an effect in the population. It represents the case when you do not reject the null hypothesis when in fact you should do because in the underlying population the null hypothesis is not true.
Imagine that you have conducted two separate studies and found a relationship between head size and IQ in study 1 and head size and shoe size in study 2. The probability of observing the relationship in study 1 by chance if the null hypothesis were true is found to be 0.04, whereas in study 2 the
How often is such a difference likely to arise by sampling error alone?(a) 1 in 5000(b) 1 in 2000(c) 1 in 500(d) 1 in 200(e) 1 in 100 Suppose the probability was 0.01: which of the above is true in this situation?
Suppose you have conducted a study looking for a difference between males and females on preference for action films. When you run your study, you find that there is a 0.005 probability of the difference you observe arising due to sampling error.
(d) We measure the relationship between the variables from our sample and then work out the probability of obtaining such a relationship by sampling error alone if the null hypothesis were true. If the probability is small, we can conclude that a genuine relationship exists in the population.
(c) We measure the relationship between the variables from our sample and then find the probability that such a relationship will arise due to sampling error alone. If such a probability is small, we can conclude that a genuine relationship exists in the population.
(b) We measure the relationship between the variables from our sample and then find the probability that such a relationship will arise due to sampling error alone.If such a probability is large, we can conclude that a genuine relationship exists in the population.
(a) We measure the relationship between the variables from our sample data. If it is large, there must be a genuine relationship in the population.
Which of the following descriptions represents a good summary of the logic behind hypothesis testing?
■ how to choose the appropriate test to analyse your data.
■ one-tailed and two-tailed hypotheses
■ the problems associated with basing conclusions on probabilities (i.e. Type I and Type II errors)
■ how probability distributions form the basis of statistical tests
■ statistical significance and how it relates to probabilities
■ the logic of hypothesis testing
The National Association of Colleges and Employers carries out a student survey each year. A summary of data from the 2009 survey included the following information:• 26% of students graduating in 2009 intended to go on to graduate or professional school.• Only 40% of those who graduated in
The article “Wait Times on Rise to See Doctor” (USA Today, June 4, 2009) gave the accompanying data on average wait times in days to get an appointment with a medical specialist in 15 U.S. cities. Construct a boxplot of the average wait-time data. Are there any outliers in the data set?City
The article “Flyers Trapped on Tarmac Push for Rules on Release” (USA Today, July 28, 2009)included the accompanying data on the number of flights with a tarmac delay of more than 3 hours between October 2008 and May 2009 for U.S. airlines.Airline Number of Flights Rate per 100,000 Flights
An automobile manufacturer who wishes to advertise that one of its models achieves 30 mpg (miles per gallon) decides to carry out a fuel efficiency test. Six nonprofessional drivers are selected, and each one drives a car from Phoenix to Los Angeles. The resulting fuel efficiencies (in miles per
Past experience has indicated that the true response rate is 40% when individuals are approached with a request to fill out and return a particular questionnaire in a stamped and addressed envelope. An investigator believes that if the person distributing the questionnaire is stigmatized in some
minutes.Is there convincing evidence that the average attention span for teenage boys is less than 5 minutes? Test the relevant hypotheses using a .01.
An article titled “Teen Boys Forget Whatever It Was” appeared in the Australian newspaper The Mercury(April 21, 1997). It described a study of academic performance and attention span and reported that the mean time to distraction for teenage boys working on an independent task was 4 minutes.
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