1.

 

In a histogram, the horizontal dimension shows:

 the possible values the variable can have.

 the intensity of the variable.

 the mean score.

 the frequency.

 

 

2.

 

Rejecting the null hypothesis at the .05 level means that:

 there is more than a 5% chance of getting such an extreme result if the null hypothesis is true.

 there is more than a 95% chance of getting such an extreme result if the research hypothesis is true.

 there is less than a 5% chance of getting such an extreme result if the null hypothesis is true.

 there is less than a 95% chance of getting such an extreme result if the research hypothesis is true.

 

3.

 

In principal, a distribution of means can be formed by:

 calculating the mean of all the possible samples of a given size and dividing it by the variance.

 using the sample's mean and variance divided by the population's parameters.

 randomly estimating the population variance from the various samples of the same size, and using the sample mean in place of µ.

 randomly taking a very large number of samples from a population, each of the same size, and making a distribution of their means.

 

 

 

 

4.

 

The variance of a distribution of means is smaller than the original population variance because:

 it is based on fewer individuals than is the original population.

 it is an estimate of the sample parameters rather than of the original population.

 extreme scores are less likely to affect a distribution of means.

 the mean of a distribution of means is so different than the population mean.

 

5.

 

Professor Q has designed a repeated measures experiment. Which information does he NOT need when looking up the power of his planned study in a power table?

 Whether a one- or two-tailed test will be computed

 Number of difference scores

 Estimated population variance of difference scores

 Effect size

 

6.

 

In an analysis of variance, if the within-groups variance estimate is about the same as the between-groups variance estimate, then:

 the null hypothesis should be rejected.

 any difference between sample means is probably due to random sampling error.

 an error has been made in computing the between-groups and the within-groups variance estimates.

 any difference between sample means is probably due to a real difference caused by experimental conditions

 

 

 

 

7.

 

In a two-way analysis of variance, the degrees of freedom for each main effect are:

 the number of cells minus the number of variables.

 the number of variables minus the total scores within the column or row.

 the number of levels of the variable minus 1

 the total number of scores in that row or column minus 2

 

8.

 

Under what conditions can an experimenter be confident that X is the cause of Y if two variables, X and Y, are strongly correlated?

 If people are randomly assigned to levels of X in a true experiment

 If people are randomly assigned to levels of Y in a true experiment

 If X is measured before Y

 If Y is measured before X

 

 

9.

 

The main difference between the test for goodness of fit and the test for independence is that:

 the goodness of fit test can be used only for 2 × 2 designs whereas the independence test is not limited to a particular design type.

 expected frequencies are calculated for the independence test but not for the goodness of fit test.

 the goodness of fit test is limited to one nominal variable whereas the independence test is not.

 observed frequencies are compared to expected frequencies for the independence test but not for the goodness of fit test.

 

 

    • 9 years ago
    A+ Answers
    NOT RATED

    Purchase the answer to view it

    blurred-text
    • attachment
      gk26.docx