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Statistics Without Maths For Psychology 7th Edition Chistine Dancey, John Reidy - Solutions
■ measures of variability in data (e.g. the standard deviation).
■ the normal distribution
■ graphical techniques for describing your data (e.g. the histogram)
■ measures of central tendency (e.g. the mean)
■ samples and populations
If you input the data as a between-participants design, then input it now as a within-participants design.
If you input the data as a within-participants design, then input it now as a between-participants design.
that the use of a grouping variable is important for between-participants designs.
how to input data for correlational, withinparticipants and between-participants designs.
about using Labels and Value Labels to make the output clearer.
how to set up variables in the Variable View part of the interface.
how to use the tutorials
■ saving data to data files.
■ setting up variables and changing variable characteristics
■ using the tutorials and help features
■ starting SPSS
Which of the following are problems associated with dichotomising continuous variables?(a) Loss of experimental power(b) Spurious effects may occur(c) There is a serious loss of information(d) All of the above
In within-participants designs, order effects occur when:(a) Participants get tired in later conditions(b) Participants perform equally well in all conditions(c) Participants have trouble obtaining their drinks at the bar(d) None of the above
Which of the following might be suitable IVs in a quasi-experimental study?(a) Gender(b) Whether or not someone had Generalised Anxiety Disorder(c) Students versus non-students(d) All of the above
Suppose you wanted to conduct a study to see if depressed individuals bite their nails more than nondepressed individuals. Which of the following would be the best way to proceed?(a) Measure participants’ depression with a questionnaire and ask them to give a rating of how much they bite their
Demand effects are possible confounding variables where:(a) Participants behave in the way they think the experimenter wants them to behave(b) Participants perform poorly because they are tired or bored(c) Participants perform well because they have practised the experimental task(d) None of the
Which of the following designs is least likely to enable us to establish causal relationships between variables?(a) Experimental design(b) Quasi-experimental design(c) Correlational design(d) Within-participants design
You have conducted a study that shows that the earlier people get up, the more work they get done.Which of the following are valid conclusions?(a) There is not necessarily a causal relationship between getting up early and amount of work done(b) People who get up early have a need to get more work
In a within-participants design with two conditions, if you do not use counterbalancing of the conditions then your study is likely to suffer from:(a) Order effects(b) Effects of time of day(c) Lack of participants(d) All of the above
A researcher has just conducted a correlational study investigating the relationship between the amount of alcohol drunk by fans of the home team before a football match and the number of goals scored by the home team. They found that there was a relationship between the two variables. Which of the
According to Streiner (2002), how efficient are studies that dichotimise continuous variables when compared with studies that do not?(a) 100%(b) 95%(c) 67%(d) 50%
Which of the following are problems associated with within-participants designs?(a) There is an increased likelihood of practice or fatigue effects(b) Participants are more likely to guess the nature of the experiment(c) They cannot be used with quasi-experimental designs(d) All of the above
A continuous variable can be described as:(a) Able to take only certain discrete values within a range of scores(b) Able to take any value within a range of scores(c) Being made up of categories(d) None of the above
Quasi-experimental designs have:(a) An IV and a DV(b) Non-random allocation of participants to conditions(c) No IV or DV(d) Both (a) and (b) above
Which of the following statements are true of experiments?(a) The IV is manipulated by the experimenter(b) The DV is assumed to be dependent upon the IV(c) They are difficult to conduct(d) Both (a) and (b) above
Between-participants designs can be:(a) Either quasi-experimental or experimental(b) Only experimental(c) Only quasi-experimental(d) Only correlational
Which of the following could be considered as categorical variables?(a) Gender(b) Brand of baked beans(c) Hair colour(d) All of the above
Which of the following are true of correlational designs?(a) They have no IV or DV(b) They look at relationships between variables(c) You cannot infer causation from correlations(d) All of the above
In a study with gender as the manipulated variable, the IV is: Lop4(a) Within participants(b) Correlational(c) Between participants(d) None of the above
Experimental designs are characterised by: Lop4(a) Fewer than two conditions(b) No control condition(c) Random allocation of participants to conditions(d) None of the above
Which of the following constitute continuous variables? Lop4(a) Number of times a score of 180 is achieved in a darts match(b) Gender(c) Temperature(d) All of the above
Experimental designs are those where the experimenter manipulates one variable called the independent variable (IV) to see what effect this has upon another variable called the dependent variable (DV).In experimental designs we are usually looking for differences between conditions of the IV. A
A confounding variable is a specific type of extraneous variable that is related to both of the main variables that we are interested in. Lop4
Which of the following are continuous, which are discrete and which are categorical?• Wind speed• Types of degree offered by a university• Level of extroversion• Makes of car• Division in which football teams play• Number of chess pieces ‘captured’ in a chess game• Weight of giant
20. Generalising to the population, what sign would the expected t-value take?(a) Positive(b) Negative(c) It could be either positive or negative
19. Which row would the researcher use to interpret the independent t-test results?(a) The equal variances row(b) The unequal variances row
18. Why are ‘all of the p values’ reported as p 6 0.001, when the other named variables have been reported with the exact probability values?(a) The researchers could not work out the exact probability values(b) The significance level in their statistical program calculated p = 0.000(c) The
17. Levene’s test is:(a) A test of heterogeneity that relies on the assumption of normality(b) A test of homogeneity that relies on the assumption of normality(c) A test of heterogeneity that does not rely on the assumption of normality(d) A test of homogeneity of variances that does not rely on
16. For a within-participants design using 20 people, the degrees of freedom are:(a) 20(b) 38(c) 19(d) 40
15. In an independent t-test, you would use the ‘equal variances not assumed’ part of the output when Levene’s test is:(a) Above a criterion significance level (e.g. p 7 0.05)(b) Below a criterion significance level (e.g. p 6 0.05)(c) When numbers of participants are unequal in the two
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)
■ the mean, standard deviation and standard error (Chapter 3)
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
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.
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