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essentials of statistics

Questions and Answers of Essentials Of Statistics

A2. This question was intentionally removed from this edition.
A1. Calculate the chi-square statistic and degrees of freedom for the following set of data for 300 elders exposed to different interventions to encourage flu shots:Is the value of chi-square
B6. Run one-way ANOVAs for two outcomes in the Polit2SetA dataset: overall satisfaction with material well-being, which is already completed if you did Exercise B1 (satovrl), and rating of
B5. For the next analysis, run a two-way ANOVA in which the dependent variable will again be satovrl, the women’s overall degree of satisfaction with their material well-being. The two dichotomous
B4. Do another one-way ANOVA for the same independent variable (hprobgrp) and dependent variable (satovrl), this time using Analyze ➜ Compare Means ➜ Means. On the second dialog box, click the
B3. Now run a one-way ANOVA with hprobgrp as the independent (group) variable, using the variable satovrl (overall satisfaction with material well-being, Variable #43) as the outcome variable. This
B2. In this exercise, you will create a new variable (call it hprobgrp) that divides the sample into three groups based on number of housing problems. The new variable will be coded 1 for no housing
B1. For these exercises, you will be using the SPSS dataset Polit2SetA, which contains a number of variables relating to material hardships and social–environmental health risks. Eight variables in
A10. This question was intentionally removed from this edition.
A9. Suppose we used a crossover design to test for differences in bruising from subcutaneous sodium heparin injections at three sites (arm, leg, and abdomen) in a sample of 15 medical–surgical
A8. Interpret the meaning of the F tests from question A7. (Note:higher scores on the self-esteem scale mean higher selfesteem.) Write a few sentences summarizing the results.
A7. Suppose we were interested in studying the self-esteem of men versus women (Factor A) in two exercise status groups—nonexercisers versus exercisers, Factor B—with 20 people in each of the
A6. For each of the following F values, indicate whether the F is statistically significant, at the specified alpha level:(a) F 2.80, df 4, 40, a .01(b) F 5.02, df 3, 60, a .001(c) F 3.45, df 3, 27,
A5. Write a few sentences that could be used to describe the results of the analyses from questions 2–4.
A4. For the data in question A2, what is the value of h2? What is the approximate estimated power for this ANOVA?Explain what the h2 and estimated power indicate.
A3. Using the data from question A2, compute three protected t tests to compare all possible pairs of means. Also, forα .05, what is the value of LSD? Which pairs are significantly different from
A2. Suppose we wanted to compare the somatic complaints (as measured on a scale known as the Physical Symptom Survey or PSS) of three groups of people: nonsmokers, smokers, and people who recently
A1. For each of the following situations, indicate whether ANOVA is appropriate; if not appropriate, the reason why not; and, if appropriate, the type of ANOVA that would be used (i.e., one-way,
B6. Run independent groups t tests for three outcomes in the Polit2SetC dataset: cesd and the two subscale score variables for the SF-12 scale. In these t tests, you will be testing the null
B5. Almost all of the data in the three datasets included are from interviews conducted with adult women in 2001, in the second wave of a longitudinal study. We have, however, included CES-D scores
B4. Using information about the pooled standard deviation for the cesd variable from the output in Exercise 1 (or from a separate “Descriptives” analysis for the cesd variable), compute the value
B3. Now run a t test to test the hypothesis, using the commands Analyze ➜ Compare Means ➜ Independent Samples T Test. Move the variable cesd into the slot for Test Variable(s). Then move the
B2. Suppose we wanted to test the hypothesis that the employment status of these disadvantaged women(i.e., whether they were working or not working at the time of the interview) was related to their
B1. For these exercises, you will be using the SPSS datasetPolit2SetC, which contains a number of mental health variables. Most of our analyses involving t tests will involve the variable cesd, which
A10. Suppose we wanted to test whether the number of hours in labor was different for women in their 20s and women
A9. The following are data for subcutaneous oxygen tension(PSCO2, measured in mmHg) 12 hours after the start of two protocols, administered to the same 10 healthy subjects in random order—a bed
A8. For a post hoc power analysis, assume that d .60, a.05 for a two-tailed t test, and the number of people in each of two groups 30. What was the approximate power of the t test, and what was the
A7. State the critical (tabled) value of t that would be used to reject the null hypothesis of equality of population means, for an independent groups t test under each of the following
A6. For each of the following t values, indicate whether the t is statistically significant for a two-tailed test, at the specified alpha:(a) t 2.40, df 25, a .01(b) t 2.40, df 25, a .05(c) t 5.52,
A5. For question A3, assume that the pooled SD for the two groups is 7.05. Calculate the value ofd. Given the result, approximately what was the power of the statistical test—and conversely,
A4. Write one or two sentences that could be used to report the results obtained for the t test in question A3.
A3. Suppose we wanted to test the hypothesis that a control group of cancer patients (Group 1) would report higher mean pain ratings than an experimental group receiving special massage treatments
A2. For which of the following situations is the dependent groups t test appropriate (if inappropriate, indicate why)?(a) The independent variable (IV) is presence or absence of conversation directed
A1. For which of the following situations is the independent groups t test appropriate (if inappropriate, indicate why)?(a) The independent variable (IV) is a type of stimulation for premature
B7. Using the variable poverty as the row variable in a Crosstabulation analysis, calculate RRs and ORs between the women’s poverty status and four to five other dichotomous outcomes of your
B6. Set up a table to display the results from Exercise B5, using Table 3 as a model. Then write a few sentences summarizing the results.
B5. This question was intentionally removed from this edition.
B4. Create a graph that presents the statistics from Exercise B3. Click on Graphs ➜ Legacy Dialogs ➜ Error Bar. The dialog box that pops up is set to a default for type of graph (Simple) that you
B3. Within Explore, you can instruct the computer to compute CIs around the means of a dependent variable for different subgroups. Run Explore for the variable bmi again, but on the opening dialog
B2. Now, have SPSS compute the same CIs around the mean of bmi by using the Analyze ➜ Descriptive Statistics ➜Explore procedure. In the opening dialog box, Insert the bmi variable into the
B1. For the exercises in this chapter, you will again be using the SPSS dataset Polit2SetB. First, run a descriptive analysis for the variable bmi, the body mass index for study participants.Do this
A10. For the problem in Question A9, would the obtained result be statistically significant with .05 for a one-tailed test (i.e., for H1: m 55)?
A9. Suppose you wanted to test the hypothesis that the average speed on a highway—where the maximum legal speed is 55 mph—is not equal to 55 mph (i.e., H0: m 55; H1: m 55). Speed guns are used to
A8. Suppose we obtained data on vein size after application of a nitroglycerin ointment in a sample of 60 patients.The mean vein size is found to be 7.8 mm with an SD of 2.5. Using the t distribution
A7. Population A and Population B both have a mean height of 70.0 inches with an SD of 6.0. A random sample of 30 people is selected from Population A, and a random sample of 50 people is selected
A6. Compute the mean, the standard deviation, and the estimated standard error of the mean for the following sample data: 3, 3, 4, 4, 4, 5, 5, 5, 5, 5, 5, 6, 6, 6, 7, and 7.
A5. If a sampling distribution of the mean had an SEM equal to 0.0, what would this suggest about the sample means drawn from the population—and about the scores in the population?
A3. Given a normal distribution of scores with a mean of 100 and an SD of 10, compute z scores for the following score values: 95, 115, 80, and 130.A4. Based on Figure 2, which shows a normal
A2. Draw a histogram that graphs the probability of drawing a spade, a club, a heart, or a diamond from a normal deck of 52 cards. Shade in the area showing the probability of drawing a red card.
A1. What is the probability of drawing a spade from a normal, shuffled deck of 52 cards? What is the probability of drawing five spades in a row (i.e., the probability of getting a flush in five-card
B6. Select several interval-level or ratio-level variables from the Polit2SetB dataset and do some basic descriptive statistics (means, SDs, etc.) for the selected variable. Then do a correlation
B5. Run crosstabs to describe the relationship between women’s current employment status and health-related characteristics in this sample of low income women, using the following variables in the
B4. Create a correlation matrix with four variables in the Polit2SetB dataset. The four variables are Variables #11, 18, 44, and 45: Number of visits to the doctor in the past 12 months(docvisit);
B3. This exercise involves producing risk index statistics, again using the dataset Polit2SetB. Run the SPSS Crosstabs procedure, using poverty status (poverty) as the risk exposure variable—i.e.,
B2. Using the same SPSS dataset (Polit2SetB), run a crosstab between poverty status (poverty) and current smoking status (smoker, Variable #15, which is coded 0 for nonsmokers and 1 for smokers).
B1. The SPSS dataset Polit2SetB has a number of healthrelated variables. Use this dataset to create a contingency table that crosstabulates the women’s poverty status (poverty, coded 1 for those
A5. Compute the correlation coefficient (Pearson’s r) to summarize the relationship for the blood pressure data presented in question A4. How accurate was your verbal description of the
A4. Below are values for diastolic and systolic blood pressure for 10 people:Diastolic 90 80 90 78 76 78 80 70 76 74 Systolic 130 126 140 118 114 112 120 110 114 116 Construct a scatterplot that
A3. The contingency table below presents fictitious data regarding an intervention to reduce pressure ulcers in nursing home residents. Using these data, compute ARE, ARNE, ARR, RR, RRR, OR, and NNT.
A2. Examine the results in Table 7. (a) Are the percentages shown in this table row percentages or column percentages? (b) Compute the percentages the opposite way, and then answer this question:
A1. The following data designate whether or not patients complied with a medication regimen (1 yes, 2 no), for an experimental group that participated in a special intervention designed to
B6. Select a variable from the Polit2SetB dataset that is an interval-level or ratio-level variable. Do some basic descriptive statistics (means, SDs, etc.) for the selected variable, and run the
B5. Run descriptive statistics on the following variables in the Polit2SetA dataset: age, age1bir, higrade, hhsize, and income. Create a table summarizing the results, using Table 2 as a model—or
B4. In this exercise, you will create a new variable (crowded)and then generate z scores for that variable. The new variable will be an index of how crowded participants were in their residences. To
B3. In this next exercise, perform analyses relating to outliers, again with the variable age1bir. Using the Explore procedure(Analyze ➞ Descriptive Statistics ➞ Explore) put age1birth into the
B2. Now, for the same variable (age1bir), determine the median, mode, and quartile values, using the Frequencies procedure (Analyze ➞ Descriptive Statistics ➞ Frequencies).When the dialog box
B1. Using the SPSS dataset Polit2SetA, determine the mean, range, standard deviation, and variance for the variable age1bir (Participants’ age at first birth). To do this, click on Analyze (on the
A5. For each blood pressure value in question A4, compute a z score. Then, transform these z scores to standard scores with a mean of 500 and an SD of 100.
A4. The following ten data values are systolic blood pressure readings. Compute the mean, the range, the SD, and the variance for these data.
A3. For which distribution in question A2 would the median be preferred to the mean as the index of central tendency?Why?
A2. Find the medians for the following distributions:(a) 1 5 7 8 9(b) 3 5 6 8 9 10(c) 3 4 4 4 6 20(d) 2 4 5 5 8 9
A1. The following numbers represent the scores of 30 psychiatric inpatients on a widely used measure of depression(the Center for Epidemiologic Studies-Depression scale).What are the mean, the
B8. Run Frequencies for the following three demographic/background variables in the dataset: educational attainment(educatn, variable number 5); currently employed (worknow, variable 7); and current
B7. To examine the issue of outliers, use the SPSS Explore command by clicking on Analyze in the top toolbar, then selecting Descriptive Statistics, then Explore. Move the variable higrade (highest
B6. Re-run the frequency distribution for higrade a third time.Now, when the initial dialog box opens, click the pushbutton for “Charts.” When a new dialog box appears, click on“Histogram”
B5. Re-run the frequency distribution for higrade. This time, when the dialog box comes up, click the pushbutton for“Statistics.” When a new dialog box appears that asks which statistics you
B4. Now focus on missing data for the variable higrade, using the same frequency distribution output as in Exercise B3.Answer these questions:(a) How many cases altogether had valid information, and
B3. Now execute the SPSS Frequency command once again for the variable higrade, highest grade of education for participants (Variable 6). (If you do this analysis right after the previous one, you
B2. Re-run the frequency distribution for racethn. This time, use the toolbar with icons that is second from the top. Put the mouse pointer over the icons, from left to right. Find the icon(likely to
B1. Using the SPSS dataset Polit2SetA, create a frequency distribution for the variable racethn. You can do this by clicking on Analyze (on the top toolbar menu), then select Descriptive Statistics
A5. If you wanted to display information on patients’ age using the data in Table 5, would you construct a histogram, bar graph, frequency polygon, or pie chart? Defend your selection, and then
A4. Describe the shape of the frequency distribution drawn in Exercise A3 in terms of modality and skewness. Is the number of falls normally distributed?
A3. Draw a frequency histogram for the data shown in Exercise A1. Now superimpose a frequency polygon on the histogram. Using a ruler, measure the height and width of your graphs: Is the height about
A2. Using information from the frequency distribution for Exercise A1, answer the following:(a) What percentage of the nursing home residents had at least one fall?(b) What number of falls was the
A1. The following data represent the number of times that a sample of nursing home residents who were aged 80 or older fell during a 12-month period. 0341020120 1001250101 0210113210 1311046101
4. Friedman and Rosenman (1974) have suggested that personality type is related to heart disease. Specifically, type A people, who are competitive, driven, pressured, and impatient, are more prone to
3. A researcher is investigating the physical characterstics that influence whether a person’s face is judged as beautiful. The reseacher selects a photograph of a woman and then creates two
2. It is well known that similarity in attitudes, beliefs, and interests plays an important role in interpersonal attraction (see Byrne, 1971, for example). Thus, correlations for attitudes between
1. The following scores are related by the equation Y = X2. Note that this is not a linear relationship, but every time X increases, Y also increases.X Y 2 4 4 16 6 36 8 64 10 100
24. Although the phenomenon is not well understood, it appears that people born during the winter months are slightly more likely to develop schizophrenia than people born at other times (Bradbury &
23. Cialdini, Reno, and Kallgren (1990) examined how people conform to norms concerning littering. The researchers wanted to determine whether a person’s tendency to litter depended on the amount
22. Research indicates that people who volunteer to participate in research studies tend to have higher intelligence than nonvolunteers. To test this phenomenon, a researcher obtains a sample of 200
21. Recent reports suggest that children who grow up with pets in the home tend to develop resistence to allergies. To test this phenomenon, a researcher interviews a sample of n 120 college
20. In a study investigating freshman weight gain, the researchers also looked at gender differences in weight(Kasparek, Corwin, Valois, Sargent, & Morris, 2008).Using self-reported heights and
19. In a study similar to one conducted by Fallon and Rozin (1985), a psychologist prepared a set of silhouettes showing different female body shapes ranging from somewhat thin to somewhat heavy and
18. Gender differences in dream content are well documented (see Winget & Kramer, 1979). Suppose a researcher studies aggression content in the dreams of men and women. Each participant reports his
17. Research results suggest that IQ scores for boys are more variable than IQ scores for girls (Arden &Plomin, 2006). A typical study looking at 10-year-old children classifies participants by
16. Earlier in this chapter, we discussed a study investigating the relationship between eyewitness memory and the questions they are asked (Loftus & Palmer, 1974).In the study, participants watched
15. The data form problem 14 show no significant difference between the opinions for city residents and those who live in the suburbs. To construct the following data, we simply doubled the sample
14. A local county is considering a budget proposal that would allocate extra funding toward the renovation of city parks. A survey is conducted to measure public opinion concerning the proposal. A

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