**Transcript and Explanation:****Study on Cortisol Levels in Corporate CEOs**An Industrial/Organizational Psychologist is planning a study focusing on cortisol levels, a biological measure of stress, in corporate CEOs. The research aims to assess stress levels before versus after a critical meeting. This meeting is vital as it is intended to prevent a hostile takeover by a larger company.**Study Details:**- **Sample Group:** The study involves 24 randomly selected CEOs from Silicon Valley.- **Measurements:** Cortisol levels are measured twice in each CEO. The first measurement takes place before the critical meeting, and the second measurement is conducted afterward.- **Hypothesis:** The psychologist predicts that the cortisol levels post-meeting will differ from those measured before the meeting.This study seeks to understand the impact of high-stakes corporate events on the stress levels of top executives. ### Independent Samples t-test#### Formula:\[ t = \frac{\sum D}{\sqrt{n(\sum D^2) - (\sum D)^2} \,/\, (n - 1)} \]- **n** = number of pairs of scores (e.g., if 8 people are measured at time 1 and time 2, df = 8-1 = 7)- **D** = difference between each pair of scores- \(\sum D\) = sum of the differences- \((\sum D)^2\) = square of the sum of differences- \(\sum (D^2)\) = sum of the differences squared#### t score:##### Formula for Independent Samples t-test (degrees of freedom = \((n_1 - 1) + (n_2 - 1)\)):\[ t = \frac{\bar{X}_1 - \bar{X}_2}{\sqrt{\frac{s_1^2}{n_1 - 1} + \frac{s_2^2}{n_2 - 1}}} \]- \(\bar{X}_1\) = mean of first group (sample)- \(\bar{X}_2\) = mean of second group (sample)- \(s_1^2\) = sample variance of first group- \(s_2^2\) = sample variance of second group- \(n_1\) = number of subjects in the first group- \(n_2\) = number of subjects in the second group**Note**: Be careful about computing the denominator; pay attention to whether you are working with sample variances or standard deviations to ensure computations are correct.### One Way ANOVA (see ANOVA table for degrees of freedom)#### Between Groups Sum of Squares:Subtract the grand mean from each group mean, square the deviation, multiply by n in each group, and add the values together.\[ SS_B = \sum n (\bar{X}_A - \bar{X}_G)^2 \]- **n** = the number of subjects or observations in a group- \(\bar{X}_A\) = the mean for any group (1 through n) of subjects- \(\bar{X}_G\) = the overall, or grand, mean for all subjects or observations

T test are usually used to compare estimates about population mean 1. Independent T test for single…

Answered: 2) An Industrial/Organizational…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Dr. Mackintosh believes a new olfactory therapy would be more successful in promoting weight loss among obese patients. His patients are first weighed and then randomly assigned to olfactory therapy, dance therapy, or a control condition. At the end of the three weeks, the amount of weight lost is recorded. The results indicate no significant difference in the amount of weight lost between the three conditions. Identify the independent variable along with each level and the dependent variable.
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.
Read the journal excerpt below:Exposure to light at night suppresses the physiologic production of melatonin, a hormone that has antiproliferative effects on intestinal cancers. Although observational studies have associated night-shift work with an increased risk of breast cancer, the effect of night-shift work on the risk of other cancers is not known. We examined the relationship between working rotating night shifts and the risk of colorectal cancers among female participants in the Nurses’ Health Study. We documented 602 incident cases of colorectal cancer among 78 586 women who were followed up from 1988 through 1998. Compared with women who never worked rotating night shifts, women who worked 15 years or more on rotating night shifts were 1.35 times more likely to develop colorectal cancer (95% CI = 1.03 to 1.77), adjusting for confounders. These data suggest that working a rotating night shift at least three nights per month for 15 or more years may increase the risk of…
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