Modern Statistics For The Social And Behavioral Sciences 2nd Edition Rand Wilcox - Solutions

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When cumulating frequencies from the top down, you typically want to discuss the data in terms of:1. “Less than”2. “At or above”3. “At most”4. All of the above
True or false: Whether you cumulate a frequency distribution from the bottom up or the top down depends on how you want to discuss the data.
When cumulating frequencies from the bottom up, you typically want to discuss the data in terms of:1. “At most”2. “Less than”3. “At or below”4. All of the above
Cumulative frequencies can be added from the top ______ and the bottom ______.
A ____________ is a summary display that distributes the sum of frequencies across a series of intervals.
Why is it generally inappropriate to include an open interval in a simple frequency distribution?
What is the recommended number of intervals that should be included in a simple frequency distribution?
Each of the following is a rule for the simple frequency distribution except:1. Each interval is equidistant.2. The same score cannot occur in more than one interval.3. Each interval is defined (it has a lower and an upper boundary).4. The interval width is equal to the number of intervals in a
True or false: A researcher observes that a single parent works 42.25 hours per week. The degree of accuracy of 42.25 is to the hundredths place (.01).
A _____________ is a summary display for a distribution of data organized or summarized in terms of how often (or frequently) scores occur.
Identify percentile points and percentile ranks in a cumulative percent distribution
Identify when it is appropriate to distribute the cumulative frequency, relative frequency, relative percent, cumulative relative frequency, and cumulative percent.
Determine whether data should be grouped or ungrouped.
Describing the scales of measurement. Landry (2015) stated, “[Scaled] data can be validly treated as interval” (p. 1348). Explain why data on a rating scale are often treated as interval scale data in the behavioral sciences.
Educational attainment and delirium. Martins, Paiva, Simões, and Fernandes (2017)conducted a study aimed to “analyze the relationship between educational attainment and delirium[i.e., a serious disturbance in mental abilities]” (p. 95). Based on the aims described for the study, what type of
Noise levels in hospital rooms. Pope (2010) conducted a study to test if noise levels measured in decibels differed in medical/surgical nursing units compared to patient rooms. She found that noise levels were substantially higher in the patient rooms compared to the nursing units. In this study,
Selecting samples from populations. Grafström and Schelin (2014) conducted a study evaluating the selection of samples from populations. They identified that “the main goal [of selecting samples] is to select a sample so that various parameters can be estimated with good precision” (Grafström
The curiosity of a child. Jirout and Klahr (2012) were interested in understanding how to characterize and study curiosity in children. In their article, they note, “Although curiosity is an undeniably important aspect of children’s cognitive development, a universally accepted [way to measure]
Gun ownership in the United States. Data from Gallup polls over a 40-year period show how gun ownership in the United States has changed. The results are described in the table below, with the percent of Americans who own guns given in each of five decades:1. Are the percentages reported here an
State whether each of the following is an example of a continuous or discrete variable.1. Time in seconds to memorize a list of words 2. Number of students in a statistics class 3. Weight in pounds of newborn infants 4. SAT scores among college students
State whether each of the following describes a study measuring a qualitative or quantitative variable.1. A researcher distributes open-ended questions to participants asking how they feel when they are in love.2. A researcher records the blood pressure of participants during a task meant to induce
A study is conducted to test whether rewarding children in a cheer camp intermittently (4 times during the camp) or once at the end of the camp differentially bolsters how much they enjoy cheering.1. Identify the independent and dependent variable in this study.2. What is the scale of measurement
A researcher tests whether mindfulness training reduces impulsive behavior in a sample of participants with a history of impulsivity.1. Identify the independent variable in this study.2. Identify the dependent variable in this study.
To determine whether a new sleeping pill was effective, adult insomniacs received a pill (either real or fake), and their sleeping times were subsequently measured (in minutes) during an overnight observation period.1. Identify the dependent variable in this study.2. Identify the independent
State whether each of the following variables is an example of an independent variable or a quasi-independent variable. Only answer quasi-independent for variables that cannot be randomized.1. Marital status 2. Political affiliation 3. Time of delay prior to recall 4. Environment of research
State whether each of the following is true or false.1. Graphs, tables, and summary statistics all illustrate the application of inferential statistics.2. Inferential statistics are procedures used to make inferences about a population, given only a limited amount of data.3. Descriptive statistics
State whether each of the following words best describes descriptive statistics or inferential statistics.1. Summarize 2. Infer 3. Describe
A qualitative variable varies by ________; a quantitative variable varies by ________.
In an experiment, researchers measure two types of variables: independent and dependent variables.1. Which variable is measured in each group?2. Which variable is manipulated to create the groups?
A researcher is interested in the effects of stuttering on social behavior with children. He records the number of peers a child speaks to during a typical school day. In this example, would the data be quantitative or qualitative?
True or false: Qualitative variables can be continuous or discrete.
State whether the variables listed in Question 2 are quantitative or qualitative.
State whether each of the following is continuous or discrete:1. Delay (in seconds) it takes drivers to make a left-hand turn when a light turns green 2. Number of questions that participants ask during a research study 3. Type of drug use (none, infrequent, moderate, or frequent)4. Season of birth
True or false: A ratio scale variable can be continuous or discrete.
For each of the following examples, (1) name the variable being measured, (2) state whether the variable is continuous or discrete, and (3) state whether the variable is quantitative or qualitative.1. A researcher records the month of birth among patients with schizophrenia. The month of birth (the
A researcher measures four variables: age (in days), speed (in seconds), height (in inches), and movie ratings (from 1 to 4 stars). Which of these variables is not an example of a variable measured on a ratio scale?
What are two characteristics of rating scales that allow researchers to use these values on an interval scale of measurement?1. Values on an interval scale have a true zero but are not equidistant.2. Values on an interval scale have differences and a true zero.3. Values on an interval scale are
In 2010, Fortune magazine ranked Apple as the most admired company in the world. This ranking is on a(n) ____________ scale of measurement.
____________ are rules for how the properties of numbers can change with different uses.
True or false: An experiment is the only method that can demonstrate cause-and-effect relationships between variables.
State whether each of the following describes an experiment, a quasi-experiment, or a correlational method.1. A researcher tests whether dosage level of some drug (low, high) causes significant differences in health.2. A researcher tests whether citizens of differing political affiliations
____________ is the study of phenomena through strict observation, evaluation, interpretation, and theoretical explanation.
A researcher conducts the following study: Participants are presented with a list of words written on a white background on a PowerPoint slide. In one group, the words are written in red (Group Color); in a second group, the words are written in black (Group Black). Participants are allowed to
True or false: Inferential statistics are used to help the researcher infer the unknown parameters in a given population.
A psychologist wants to study a small population of 40 students in a local private school. If the researcher was interested in selecting the entire population of students for this study, then how many students must the psychologist include?1. None, because it is not possible to study an entire
__________ describe(s) characteristics in a population, whereas _____________ describe(s)characteristics in a sample.1. Statistics; parameters 2. Parameters; statistics 3. Descriptive; inferential 4. Inferential; descriptive
_____________ are procedures used to summarize, organize, and make sense of a set of scores, called data.
On the basis of the following example, we will identify the population, sample, population parameter, and sample statistic: Suppose you read an article in the local college newspaper citing that the average college student plays 2 hours of video games per week. To test whether this is true for your
Distinguish between continuous and discrete variables.
Distinguish between quantitative and qualitative variables.
State the four scales of measurement and provide an example for each.
Describe three research methods commonly used in behavioral science.
Explain how samples and populations, as well as a sample statistic and population parameter, differ.
Using the plasma retinol data in Section 1.3.3, and removing leverage points, ignore the former smokers and use the R function logrsm to estimate the likelihood that a participant was never a smoker given their plasma beta-carotene value.Does this suggest that a basic logistic model is reasonable?
For the data in Table 15.6, verify that odds ratio is 0.4776119.
For the data in Exercise 7, determine which if any of the claimed cell probabilities appear to be incorrect using the R function binomci. Use the Bonferroni method with the goal that the probability of one or more Type I errors will be at most 0.05.
Someone claims that the proportion of adults getting low, medium, and high amounts of exercise is 0.5, 0.3, and 0.2, respectively. To check this claim you sample 100 adults and find that 40 get low amounts of exercise, 50 get medium amounts, and 10 get high amounts. Test the claim with α = 0.05.
Compute kappa for the data in Exercise 5.What does this estimate tell you?
You observeEstimate the proportion of agreement, and compute a 0.95 confidence interval using the R function binomci. Income (daughter) High Medium Low Total Income (father) High Medium Low Total 30 50 20 100 50 70 30 150 10 20 40 70 90 140 90 320
In Exercise 1, estimate the odds ratio and interpret the results.
In Exercise 1, would you reject the hypothesis that income and outlook are independent? Use α = 0.05. Would you use the φ coefficient to measure the association between income and outlook? Why?
Referring to the previous exercise, compute a 0.95 confidence interval for δ =p1+ − p+1. Test H0: p12 = p21.
You randomly sample 200 adults, determine whether their income is high or low, and ask them whether they are optimistic about the future. The results areWhat is the estimated probability that a randomly sampled adult has a high income and is optimistic? Compute a 0.95 confidence interval for the
For the Well Elderly 2 data in the file B3 dat.txt, use the R function ancova to compare males and females based on the variable MAPAGLOB (meaningful activities) using PEOP (personal support) as a covariate.
R has a built-in data set called leuk. The third column indicates survival times, in weeks, for patients diagnosed with acute myelogenous leukemia. The first column indicates the patient’s white blood cell count at the time of diagnosis. Compute Pearson’s correlation and compare the results to
Repeat the previous exercise, only now use the R function ancova to compare the regression lines. At which X values do you get a significant difference withα = 0.05? Compute the adjusted p-values.
For the Well Elderly 2 data in Exercises 4 and 6, compare the regression lines using ancJN using the data labeled CESD (depressive symptoms) as the independent variable and LSIZ as the dependent variable. Use the data in the file A3 for the first group (the experimental group) and the file B1 as
For the data in the previous exercise, what might be affecting the test that there is curvature. Use R to check on this possibility?
The author’s web page contains the file skull data.txt, which contains data reported by Thompson and Randall-Maciver (1905) dealing with skull measurements of male Egyptians from different time periods. The four measurements are contained in the first four columns and the time period is indicated
Repeat Exercise 4, only use the data in the file B3 dat.txt. Comment on the results.
For the data in the previous exercise, test the hypothesis that the 0.8 quantile regression line has a zero slope with leverage points removed.
A portion of the data from the Well Elderly 2 study is stored in the author’s web page in the file A3 dat.txt. These are measures taken after intervention. Use the R function qhdsm to create a smooth for the 0.2, 0.5, and 0.8 quantiles using the data with the label MAPAGLOB as the independent
Repeat the previous exercise, only use the data in column one as the independent variable.
Table 6.4 reports data on 29 lakes in Florida and are stored in the file lake dat.txt on the author’s web page. Assuming that you want to predict Y (the mean annual nitrogen concentration stored in column two) given TW (water retention time stored in column three), plot a smooth using the R
For the predictor X2 in Table 14.2, if the R function runYhat is used to estimate the typical value of Y given that X2 = 250, based on a 20% trimmed mean, the function returns NA. Explain why this occurs.
For the plasma data in Chapter 1, use the function mat2grp to sort the data into two groups based on whether a participant is male or female. Compare these two groups in terms of dietary beta-carotene consumed (labeled BETADIET)and dietary retinol consumed (labeled RETDIET) using the R function
For the data used in the previous two exercises, verify that the R functions outpro and outproad identify the same points as outliers. Why was this expected?
Using the data generated in the previous exercise, compute the principal component scores and verify that the corresponding correlation matrix is approximately equal to the identity matrix.
Using R, generate data and store it in the R variable x using the commands set.seed(3)x=rmul(100,p=5,mar.fun=ghdist,h=0.2,rho=0.7)x[,1]=rlnorm(100)This creates five random variables, the last four of which have symmetric, heavytailed distributions with a common correlation of 0.7. The first
Repeat the example in Section 13.3.1 based on the skull data, only use the final skull measures rather than the first two.
Consider a bivariate data set and imagine that the data are projected onto the x-axis and then checks for outliers are made using the MAD-median rule. The same is done when projecting the data onto the y-axis and both times no outliers are found. Why might the conclusion of no outliers be
Among the five groups in the previous exercise, only one group was found to have an outlier based on the boxplot rules in Chapter 2.What might explain why more significant differences are found when comparing groups based on 20% trimmed means versus the mean?
Thompson and Randall-Maciver (1905) report four measurements of male Egyptian skulls from five different time periods. The first was maximal breadth of skull and the five time periods were 4000 BC, 3300 BC, 1850 BC, 200 BC, and 150 AD. The data are stored on the author’s web site in the file
Perform all pairwise comparisons of the groups in Table 10.1 using the R function rmmcppb. First use the default estimator, which is a one-step M-estimator and then use the MOM estimate of location. Use difference scores. Note that when using a one-step M-estimator, NA is returned for the p-values
For the four groups in Table 10.1, use the R functions apply and bootse to compute the standard errors for the Harrell–Davis estimator, which is computed with the R function hd. Compare the results to the estimated standard error for the 20% trimmed means returned by trimse.
Use the R function msmed to compare all pairs of groups based on medians using the data in Table 10.1. Note that the function prints a warning that there are tied values in group 3, and suggests using the R function medpb. Use this function and compare the results to those returned by msmed.
Use the R function lincon to verify that for the data in Table 10.1, the hypothesis of equal 20% trimmed means is rejected for groups 3 and 4, with FWE equal to 0.05, but otherwise no differences are found.
Repeat the previous exercise using the R function hochberg in Section 12.3.4.Verify that the required sample sizes are 50, 10, 18, and 17 when using means.Compare this to using 20% trimmed means.
For the data in Table 9.1, each group has 10 observations, so when using Tamhane’s method to compute confidence intervals for all pairwise differences, the degrees of freedom are 9 and the value of h in Table 11 of Appendix B is 4.3.Verify that if the goal is to have confidence intervals with FWE
Repeat the previous exercise but with the Tukey–Kramer and Scheff´e methods instead.
Imagine you compare four groups with Fisher’s method and you reject the hypothesis of equal means for the first two groups. If the largest observation in the fourth group is increased, what happens to MSWG? What does this suggest about power when comparing groups one and two with Fisher’s
Referring to the previous exercise, which would be rejected with Rom’s procedure?
You perform five tests and get p-values 0.049, 0.048, 0.045, 0.047, and 0.042.Based on the Bonferroni inequality, which would be rejected with FWE equal to 0.05?
For the previous exercise, if you use Rom’s method, which tests would be rejected?
You perform six tests and get the p-values 0.07, 0.01, 0.40, 0.001, 0.1, and 0.15.Based on the Bonferroni inequality, which would be rejected with FWE equal to 0.05?
Repeat the previous exercise, but now with n1 = n2 = n3 = n4 = n5 = 10, X¯1 = 20, X¯2 = 12, s 21 = 5, s 22 = 6, s 23 = 4, s 24 = 10, and s 25 = 15.
For five independent groups, assume that you plan to do all pairwise comparisons of the means and you want FWE to be 0.05. Further assume that n1 = n2 = n3 =n4 = n5 = 20, X¯1 = 15, X¯2 = 10, s 21 = 4, and s 22 = 9, s 23 = s 24 = s 25 = 15.Test H0 : µ1 = µ2 using (a) Fisher’s method (assuming
Assuming normality and homoscedasticity, what problem occurs when comparing multiple groups with a Student’s T test and the groups have a common mean?
For the data used in Exercise 1, use the R function sppbi to test the hypothesis of no interactions based on a 20% trimmed mean. Verify that the p-value is 0.04.How does this compare to using a one-step M-esitmator?
Compare the results from the previous three exercises and comment on finding the optimal method for detecting a true difference among groups.

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Modern Statistics For The Social And Behavioral Sciences 2nd Edition Rand Wilcox - Solutions

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