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Statistics For The Behavioral Sciences 2nd Edition Susan A. Nolan, Thomas Heinzen - Solutions
What is bootstrapping?
If your data meet the assumptions of the parametric test, why is it preferable to use the parametric test rather than the nonparametric alternative?
Define and explain the symbols in the following equation:
When is it appropriate to use the Kruskal–Wallis H test?
How are the critical values for the Mann–Whitney U test and the Wilcoxon signed-rank test used differently than critical values for parametric tests?
What are the assumptions of the Mann–Whitney U test?
When do we use the Mann–Whitney U test?
When is it appropriate to use the Wilcoxon signed-rank test?
How is N determined for the Wilcoxon signed-rank test and how does this differ from the way N is typically determined for most statistical tests?
What is the possible range of values for the Spearman rank-order correlation and how are these values interpreted?
Define the symbols in the following term: rS
Explain how the relation between ranks is the core of the Spearman rank-order correlation.
What does a histogram of rank-ordered data look like and why does it look that way?
How does the transformation of scale data to ordinal data solve the problem of outliers?
When the data on at least one variable are ordinal, the data on any scale variable must be converted from scale to ordinal. How do we convert a scale variable into an ordinal one?
When do we convert scale data to ordinal data?
Refer to the study of poor growth in children from Exercise 17.37. Below is a printout from SPSS software that depicts the data for the six cells. For each cell, there is an observed frequency (count), expected frequency(expected count), and adjusted standardized residual (adjusted residual).
In How It Works 17.2, we walked through a chi-square test for independence using two items from the General Social Survey (GSS)—LIFE and MOBILE16. Use these data to answer the following questions.
Refer to the study of poor growth in children from Exercise 17.37. Consider only those boys and girls who were below norms for their age groups. That is, ignore those who turned out to have normal heights according to growth charts.a. Among only children who are below height norms, calculate the
Refer again to the prisoner’s dilemma example from Exercise 17.36.a. Calculate the relative risk (or relative likelihood) of defecting given that one is from China versus the United States. Show your calculations.b. Explain what we learn from this relative risk.c. Now calculate the relative risk
In Check Your Learning 17-8, we introduced the example of the Chicago Police Department’s study of lineups. Below is a printout from SPSS software that depicts the data for the six cells.a. For simultaneous lineups, what is the observed frequency for the identification of suspects?b. For
Refer to the study of poor growth in children in Exercise 17.37.a. Draw a table that includes the conditional proportions for boys and for girls.b. Create a graph with bars showing the proportions for all six conditions.
Refer to the prisoner’s dilemma example in Exercise 17.36.a. Draw a table that includes the conditional proportions for participants from China and from the United States.b. Create a graph with bars showing the proportions for all four conditions.c. Create a graph with two bars showing just the
Grimberg, Kutikov, and Cucchiara (2005) wondered whether gender biases were evident in referrals of children for poor growth. They believed that boys were more likely to be referred even when there was no problem—bad for boys because families of short boys might falsely view their height as a
In a classic prisoner’s dilemma game with money for prizes, players who cooperate with each other both earn good prizes. If, however, your opposing player cooperates but you do not (the term used is defect), you receive an even bigger payout and your opponent receives nothing. If you cooperate
Richards (2006) reported data from a study by the American Prospect on the genders of op-ed writers who addressed the topic of abortion in the New York Times.Over a two-year period, the American Prospect counted 124 articles that discussed abortion (from a wide range of political and ideological
Across all of India, there are only 933 girls for every 1000 boys (Lloyd, 2006), evidence of a bias that leads many parents to illegally select for boys or to kill their infant girls. (Note that this translates into a proportion of girls of 0.483.) In Punjab, a region of India in which residents
“Do Immigrants Make Us Safer?” asked the title of a New York Times Magazine article (Press, 2006). The article reported findings from several U.S.-based studies, including several conducted by Harvard sociologist Robert Sampson in Chicago. For each of the following findings, draw the table of
Here are three ways to assess one’s performance in high school: (1) GPA at graduation, (2) whether one graduated with honors (as indicated by graduating with a GPA of at least 3.5), and (3) class rank at graduation.For example, Abdul had a 3.98 GPA, graduated with honors, and was ranked 10th in
A New York Times article on grade inflation reported several findings related to a tendency for average grades to rise over the years and a tendency for the top-ranked institutions to give the highest average grades (Archibold, 1998). For each of the findings outlined below, state (i) the
Weinberg, Fleisher, and Hashimoto (2007) studied almost 50,000 students’ evaluations of their professors in almost 400 economics courses at The Ohio State University over a 10-year period. For each of their findings, outlined below, state (i) the independent variable or variables, and their
For each of the following research questions, state whether a parametric or nonparametric hypothesis test is more appropriate. Explain your answers.a. Are women more or less likely than men to be economics majors?b. At a small company with 15 staff and 1 top boss, do those with a college education
The following table (output from SPSS) represents the observed frequencies for the data presented in Exercise 17.22 and the adjusted standardized residuals for each of the cells. Using this information and the criterion of 2, indicate for which of these cells there is a significant difference
The data below are from a study of lung cancer patients in Turkey (Yilmaz et al., 2000). Use these data to calculate the relative likelihood of being a smoker given that a person is female rather than male.
Use the data presented in Exercise 17.22 to calcu late the relative likelihood of accidents given that it is raining.
Calculate the appropriate measure of effect size for the data presented in Exercise 17.22 and the statistic calculated in Exercise 17.24.
Using the data presented in Exercise 17.22 and the work you did in Exercise 17.23, calculate the test statistic.
Using the data presented in Exercise 17.22, complete this table of expected frequencies.
Below are some data to use in a chi-square test for independence. Calculate the degrees of freedom for this test.
Use this calculation table for the chi-square test for goodness-of-fit to complete this exercise.a. Calculate degrees of freedom for this chi-square test for goodness-of-fit.b. Perform all of the calculations to complete this table.c. Compute the chi-square statistic.
Use this calculation table for the chi-square test for goodness-of-fit to complete this exercise.
For each of the following, identify the independent variable(s), dependent variable(s), and the level of measurement (nominal, ordinal, scale).a. The number of loads of laundry washed per month was tracked for women and men living in college dorms.b. A researcher interested in people’s need to
For each of the following, (i) identify the incorrect symbol, (ii) state what the correct symbol should be, and (iii) explain why the initial symbol was incorrect.
How are adjusted standardized residuals used as a post-hoc test for chi-square tests?
How are adjusted standardized residuals cal -culated?
What is the difference between relative likelihood and relative risk?
In order to calculate relative likelihood, what must be calculated first?
What information does the measure of relative likelihood provide?
What is the formula used for?
Define the symbols in the following formula: v2
What measure of effect size is used with chi square?
What information is presented in a contingency table in the chi-square test for independence?
Why is there just one critical value for a chi-square test, even when the hypothesis is a two-tailed test?
How are the degrees of freedom for the chi-square hypothesis tests different from those of most other hypothesis tests?
What are the hypotheses when conducting the chisquare test for goodness-of-fit?
List two ways in which statisticians use the word independence or independent with respect to concepts introduced earlier in this book. Then describe how independence is used by statisticians with respect to chi square.
What are the four assumptions for the chi-square tests?
What is the difference between the chi-square test for goodness-of-fit and the chi-square test for independence?
What are the three main situations in which we use a nonparametric test?
Distinguish nominal, ordinal, and scale data.
The attached figure is from a journal article entitled“Neighborhood Social Disorder as a Determinant of Drug Injection Behaviors: A Structural Equation Modeling Approach” (Latkin, Williams, Wang, & Curry, 2005).a. What are the four latent variables examined in this study?b. What manifest
Consider again the example used in Exercise 16.54. As before, the researcher is interested in predicting mathematics ability with the ultimate goal of identifying ways to improve mathematics performance.a. How would you develop the multiple regression equation using stepwise multiple regression?
Using the data about political contributions and corporate profits, and your work from Exercise 16.48, answer the following questions:a. Compute the standardized regression coefficient.b. How does this coefficient relate to other information you know?c. Draw a conclusion about your analysis based
We conducted a second regression analysis on the data from Exercise 16.56. In addition to depression at year 1, we included a second independent variable to predict anxiety at year 3. We also included anxiety at year 1. (We might expect that the best predictor of anxiety at a later point in time is
Using the data about age and number of hours studied, and your work from Exercise 16.47, answer the following questions:a. Compute the standardized regression coefficient.b. How does this coefficient relate to other information you know?c. Draw a conclusion about your analysis based on what you
We analyzed data from a larger data set that one of the authors used for previous research (Nolan, Flynn, &Garber, 2003). In the current analyses, we used re -gression to look at factors that predict anxiety over a three-year period. Shown below is the output for the regression analysis examining
Consider again the example used in Exercise 16.54.As before, the researcher is interested in predicting mathematics ability with the ultimate goal of identifying ways to improve mathematics performance. If you were to develop a multiple regression equation instead of a simple linear regression
A researcher conducted a study in which children with problems learning mathematics were offered the opportunity to purchase time with special tutors. The number of weeks that children met with their tutuors varied from 1 to 20. He found that the number of weeks of tutoring predicted mathematics
Are podcasts a drain on students’ time, or does the information they contain help students do better in school? You collect data on the number of pod -casts each student downloads per month and each student’s GPA. When we calculate regression equations(just as when we calculate cor relation
Does the level of precipitation predict violence? Dubner and Levitt (2006b) reported on various studies that found links between rain and violence. They mentioned one study by Miguel, Satyanath, and Sergenti that found that decreased rain was linked with an increased likelihood of civil war across
Does one’s cola consumption predict one’s bone mineral density? Using regression analyses, nutrition researchers found that older women who drank more cola(but not more of other carbonated drinks) tended to have lower bone mineral density, a risk factor for osteoporosis (Tucker, Morita, Qiao,
Exercises 16.45, 16.47, and 16.49 used the example from How It Works 15.2 on the relation between age and how much people study. Here are the data once againa. Calculate the proportionate reduction in error the long way.b. Explain what the proportionate reduction in error that you calculated in
Exercises 16.45 and 16.47 used the example from How It Works 15.2 on the relation between age and how much people study.a. Construct a graph that includes both the scatterplot for these data and the regression line as determined in Exercise 16.47. Draw vertical lines to connect each dot on the
Researchers studied whether corporate political contributions predicted profits (Cooper, Gulen, & Ovtchinnikov, 2007). From archival data, they determined how many political candidates each company supported with financial contributions, as well as each company’s profit in terms of a percentage.
Exercise 16.45 used the example from How It Works 15.2 on the relation between age and how much people study. Recall that the mean for age is 21, and the standard deviation is 1.789. The mean for hours studied is 14.2, and the standard deviation is 5.582. The correlation coefficient is 0.49.a.
A regression analysis of data from some of our statistics classes yielded the following regression equation for the independent variable, hours studied, and the dependent variable, grade point average (GPA): Yˆ 2.96 0.02(X).a. If you plan to study 8 hours per week, what would you predict for your
In How It Works 15.2, we calculated the correlation coefficient between students’ age and number of hours they study per week. The mean for age is 21, and the standard deviation is 1.789. The mean for hours studied is 14.2, and the standard deviation is 5.582. The correlation between these two
The verbal subtest of the Graduate Record Exami -nation (GRE) has a population mean of 500 and a population standard deviation of 100 by design (the quantitative subtest has the same mean and standard deviation).a. Convert the following z scores to raw scores without using a formula: (i) 1.5, (ii)
A study of Consideration of Future Consequences(CFC) found a mean score of 3.51, with a standard deviation of 0.61, for the 664 students in the sample(Petrocelli, 2003).a. Imagine that your z score on the CFC score was 1.2. What would your raw score be? Use symbolic notation and the formula.
In How It Works 15.2, we calculated the correlation coefficient between students’ age and number of hours they study per week. The correlation between these two variables is 0.49.a. Elif’s z score for age is 0.82. What would we predict for the z score for the number of hours she studies per
Running a football stadium involves innumerable predictions. For example, when stocking up on food and beverages for sale at the game, it helps to have an idea of how much will be sold. In the football sta -diums in colder climates, stadium managers use expected outdoor temperature to predict sales
Several studies have found a correlation between weight and blood pressure.a. Explain what is meant by a correlation between these two variables.b. If you were to examine these two variables with simple linear regression instead of correlation, how would you frame the question? (Hint: The research
Refer to the structural equation model (SEM) depicted in Figure 16-9:a. Which two variables are most strongly related to each other?b. Is positive parenting at age 17 directly related to emotional adjustment at age 26? How do you know?c. Is positive parenting at age 17 directly related to identity
Assume that a researcher is interested in variables that might affect infant birth weight. The researcher performs a stepwise multiple regression to predict birth weight and includes the following independent variables: (1) number of cigarettes the mother smokes per day, (2) number of alcoholic
Compute the standardized regression coefficient for the data presented in Exercise 16.31. Remember, r 0.52, and the regression equation is: Yˆ2.643 0.469(X). X Y 4.00 6.00 6.00 3.00 7.00 7.00 8.00 5.00 9.00 4.00 10.00 12.00 12.00 9.00 14.00 8.00 Mx=8.75 My = 6.75 SDx 3.031 SD = 2.727
Compute the standardized regression coefficient for the data presented in Exercise 16.30. Remember, r 0.426, and the regression equation is Yˆ 219.974 186.595(X).
Use the equation for the line you created in Exercise 16.33 to make predictions for each of the following:a. SAT 1030, rank 41b. SAT 860, rank 22c. SAT 1060, rank 8
to make predictions for each of the following:a. Variable 1 6, variable 2 60b. Variable 1 9, variable 2 54.3c. Variable 1 13, variable 2 44.8
Use the equation for the line you created in Exercise
Write the equation for the line of prediction using the following output from a multiple regression analysis: Coefficients Unstandardized Coefficients Standardized Coefficients Model 1 B Std. Error Beta t Sig. (Constant) 1.675 .563 2.972 .004 SAT .001 .000 .321 2.953 .004 Rank -.008 .003 -279
Write the equation for the line of prediction using the following output from a multiple regression analysis: Coefficients Unstandardized Coefficients Standardized Coefficients Model B Std. Error Beta t Sig. 1 (Constant) 3.977 1.193 3.333 .001 Variable 1 .414 .096 .458 4.313 .000 Variable 2 -.019
Data are provided here with descriptive statistics, a correlation coefficient, and a regression equation: r 0.52, Yˆ 2.643 0.469(X).Using this information, compute the following estimates of prediction error:a. Calculate the sum of squared error for the mean, SStotal.b. Now, using the regression
Data are provided here with descriptive statistics, a correlation coefficient, and a regression equation: r 0.426, Yˆ 219.974 186.595(X). Using this information, compute the following estimates of prediction error:a. Calculate the sum of squared error for the mean, SStotal.b. Now, using the
Using the following information from Exercise 16.25, complete the following:Age is related to bone density, with a Pearson coefficient of 0.19.Age of people studied: 55 years on average, with a standard deviation of 12 years Bone density of people studied:1000 mg/cm2 on average, with a standard
Using the following information from Exercise 16.24, complete the following:Var iable X: M 12, SD 3 Var iable Y: M 74, SD 18 Pearson correlation of variables X and Y 0.46a. Calculate the y intercept, a.b. Calculate the slope, b.c. Write the equation for the line.d. Draw the line on an empty
Given the regression line Yˆ 49 0.18(X), make predictions for each of the following:a. X 31b. X 65c. X 14
Let’s assume we know that age is related to bone density, with a Pearson correlation coefficient of 0.19.(Notice that the correlation is negative, indicating that bone density tends to be lower at older ages than at younger ages.) Assume we also know the following descriptive statistics:Age of
Using the following information, make a prediction for Y given an X score of 8:Var iable X: M 12, SD 3 Var iable Y: M 74, SD 18 Pearson correlation of variables X and Y 0.46a. Transform the raw score for the independent variable to a z score.b. Calculate the predicted z score for the dependent
What is the difference between a latent variable and a manifest variable?
How does structural equation modeling (SEM) differ from multiple regression?
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