40 terms

Chp 13

Final exam
__________ are used to infer that the results from a sample are reflective of the true population scores.
Inferential statistics
When comparing group means, the _________ states that group means are equal.
Null hypothesis
The F statistic is a ratio of two types of variance: __________ variance and error variance.
Cohen's d expresses effect size in terms of _________.
Standard deviation units
A Type I error occurs when the null hypothesis is _________.
Rejected but the null hypothesis is actually true
Which of the following statements is TRUE?
True differences are more likely to be detected if the sample size is large.
If a mechanic looks at your car engine and says there is nothing wrong with it and your car breaks down when you leave the garage, what type of error did the mechanic make?
Type II
If the null hypothesis was rejected and there was 1 chance out of 100 that the decision was wrong, what was the alpha level in the study?
Which of the following is NOT a reason for a Type II error?
Large sample size
Dr. P is using a t-test to compare the means of two groups. There are 25 participants in each group. How many degrees of freedom are there in this test?
How is the power of a statistical test related to the probability of a Type II error?
Power = 1- Type II error
Which of the following is NOT a major statistical software program?
If the null hypothesis is correct, then the research hypothesis is accepted as correct.
The null hypothesis is rejected when there is a very low probability that the obtained results could be due to random error
The probability required for significance is called the alpha level.
The t-test is most commonly used to examine whether two groups are significantly different from each other.
Error variance is the deviation of the group means from the grand mean.
A .05 significance level indicates that there is a 95% chance that the research findings are incorrect.
The probability of making a Type I error is determined by the choice of alpha level.
Nonsignificant results do not necessarily indicate that the null hypothesis is correct.
Chi-square tests are used in the case of ordinal scale data
The Kruskal Wallace H test and the Mann-Whitney U test are both appropriate significance tests for interval scale data.
Researchers conducted a naturalistic observation to examine gender differences in manners. Standing outside the bookstore, the researchers observed men and women leaving the bookstore and recorded when they held the door open or did not hold the door open for another person.
Chi-square test
Participants were recruited to participate in a memory study. Participants were randomly assigned to the learn a list of words printed on either white paper with red ink or white paper with black ink. The number of words correctly recalled was recorded.
Between-subjects t-test
Researchers examined the influence of different types of rewards on creative expression. Children were given an art kit and asked to create a collage. Students were randomly assigned to one of three experimental conditions: monetary reward, toy reward, or control. Each collage was given points for use of color, originality, structure, and design. The total number of points was recorded.
One-way Between-Subjects Analysis of Variance
A study is done to determine whether dieting plus exercise is more effective for producing weight loss than dieting alone. Participants were matched on initial weight, initial level of exercise, age, and gender. One member of each pair was put on the diet for 2 months. The other member had the same diet but exercised moderately each week. The weight loss in pounds for the 2-month period was recorded.
Repeated Measures (correlated) t-test
Suppose a researcher studied men's shoe size and the mode of delivery of their first child. The researcher collected and classified shoe size data on 600 first-time fathers into three groups: large (size 10 and above), average (size 8 and 9), and small (size 7 and smaller).
Kruskal-Wallace H test
Suppose researchers conducted a study and ranked salespeople according to the number of automobiles they sold the past six months. The rankings of the top 20 salespeople were separated into two groups--those who valued time management and those who did not value time management.
Mann-Whitney U test
Degrees of freedom
A concept used in tests of statistical significance; the number of observations that are free to vary to produce a known outcome.
Error variance
Random variability in a set of scores that is not the result of the independent variable. Statistically, the variability of each score from its group mean.
Inferential statistics
Statistics designed to determine whether results based on sample data are generalizable to a population.
Null hypothesis
The hypothesis, used for statistical purposes, that the variables under investigation are not related in the population, that any observed effect based on sample results is due to random error.
The probability of correctly rejecting the null hypothesis.
The likelihood that a given event (among a specific set of events) will occur.
Research hypothesis
The hypothesis that the variables under investigation are related in the population—that the observed effect based on sample data is true in the population.
Statistical significance
Rejection of the null hypothesis when an outcome has a low probability of occurrence (usually .05 or less) if, in fact, the null hypothesis is correct.
Systematic variance
Variability in a set of scores that is the result of the independent variable; statistically, the variability of each group mean from the grand mean of all subjects.
A statistical significance test used to compare differences between means.
Type I error
An incorrect decision to reject the null hypothesis when it is true.
Type II error
An incorrect decision to reject the null hypothesis when it is true.