Chapter 13, Problem 13.13AC

Suppose that, as part of a research methods class, Bailey was asked to write a summary of a research paper on the topic of the effects of visitor traffic on the relative humidity in bat caves.                        Identify the explanatory and the response variables.                                                                                                                                                                                                                                                         The number of visitors and the relative humidity are the response variables. The number of visitors is the response variable, and the relative humidity is the explanatory variable. The number of visitors and the relative humidity are the explanatory variables. The number of visitors is the explanatory variable, and the relative humidity is the response variable.

For each of the following epidemiological scenarios, draw a DAG that represents the relationships between the variables: A researcher is studying the association between experiencing childhood abuse (A) and the occurrence of depression (D) as an adult. She has reason to believe that alcohol consumption (C) may mediate the relationship between (A) and (D).

If the coefficient of determination between two independent variables is 0.23​, what is the​ VIF?

8.6 Cherry Trees:  Timber yield is approximately equal to the volume of a tree, however, this value is difficult to measure without first cutting the tree down. Instead, other variables, such as height and diameter, may be used to predict a tree's volume and yield. Researchers wanting to understand the relationship between these variables for black cherry trees collected data from 31 such trees in the Allegheny National Forest, Pennsylvania. Height is measured in feet, diameter in inches (at 54 inches above ground), and volume in cubic feet. (Hand, 1994)   Estimate Std. Error t value P(>|t|) (Intercept) -57.99 8.64 -6.71 0.00 height 0.34 0.13 2.61 0.01 diameter 4.71 0.26 17.82 0.00

A researcher is interested in the relationship between levels of stress at work and self-reports of overall health. Stress at work is measured on a scale from 0 (no stress at work) to 100 (extreme levels of stress at work). The researcher conducts a study with 11 subjects and determines that the relationship between self-reports of stress and self-reports of overall heath is r = -.41. The results from this study resulted in p > .05, therefore the investigator should: a. fail to reject the null, there was a significant linear relationship between stress and health b. fail to reject the null, there was not a significant linear relationship between stress and health c. reject the null, there was a significant linear relationship between stress and health d. reject the null, there was not a significant linear relationship between stress and health     NEW STUDY: Dr. Apnea conducted a study investigating the effects of sleep deprivation on complex problem solving. He gave 25…

The authors of a paper compared two different methods for measuring body fat percentage. One method uses ultrasound, and the other method uses X-ray technology. Body fat percentages using each of these methods for 16 athletes (a subset of the data given in a graph that appeared in the paper) are given in the accompanying table. You can assume that the 16 athletes who participated in this study are representative of the population of athletes. Athlete X-ray Ultrasound 1 5.00 4.50 2 15.00 11.75 3 9.25 9.00 4 12.00 11.75 5 17.25 17.00 6 29.50 27.50 7 5.50 6.50 8 6.00 6.75 9 8.00 8.75 10 16.50 17.50 11 9.25 9.50 12 11.00 12.00 13 12.00 12.25 14 14.00 15.50 15 17.00 18.00 16 18.00 18.25   Use these data to estimate the difference in mean body fat percentage measurement for the two methods. Use a confidence level of 95%. (Use ?d = ?X-ray − ?ultrasound. Round your answers to three decimal places.)     ,     % Interpret the interval in…

The marketing manager of a chain of stores needed information about theeffectiveness of television advertising on weekly sales. The manager collected data from 25 randomly selected stores. For each store, the variables “store sales” and “TV advertising” were recorded per week.Both variables are recorded in euros (i.e. 1 unit=€1).You are given the following SPSS output.  please see Image attached. Answer the following questions:(1) Test if television advertising generally affects the sales of this store. Use a 5% level of significance.(2) Write down the estimated regression model and interpret the coefficients. (3) Write down the value of the coefficient of determination and explain it. Is the fitting ofyour regression model good?(4) What is the value of the correlation coefficient between weekly sales and weeklyexpenditures on television advertising? Interpret it.(5) Predict the weekly sales when television advertising is €700.

Please make sure the response is specific to the variables in this problem: Imagine that you are interested in studying the working habits of young adults. You hypothesize that persons first married in their twenties tend to work an average of 5 hours more per week than persons not first married in their twenties. After conducting a survey study, you find a relationship between participants’ age at first marriage and the number of hours worked per week. What three conditions must be satisfied for you to have established a causal connection?

Q1. A psychologist conducted a study on the relationship between introversion and shyness. The values are results for scales of introversion and shyness. High positive scores on each scale indicate high introversion or shyness; and high negative scores indicate low introversion or shyness. Data collected from 10 people as follows: Introversion 4 -7 -1 0 6 7 -4 -9 -5 8 Shyness 11 -7 -1 -3 0 7 -1 -8 -1 5 a) Compute the correlation coefficient relating introversion and shyness scores. b) Find the regression equation which predicts introversion from shyness. c) What introversion score would you predict from a shyness score of 7?