Imagine that a professor of psychology has two teaching assistants (TAs) who will help her grade assignments for the duration of the semester. The professor wants to make sure that she and the TAs are well calibrated with one another, so she has all three of them grade the first assignment independently. Because the professor grades every assignment on a curve, she first converts the students’ scores to z-scores for each grader. The following table shows the z-scores for a population of 10 students in her class for each grader.   Professor Teaching Assistant #1 Teaching Assistant #2 Student 1 0.70 1.27 1.27 Student 2 0.83 -0.64 -1.55 Student 3 -0.98 0.38 -0.14 Student 4 2.21 0.80 0.92 Student 5 -0.54 -1.34 -1.06 Student 6 0.43 0.10 0.30 Student 7 -1.03 -2.09 -1.50 Student 8 -0.01 0.85 1.14 Student 9 -0.54 0.48 0.57 Student 10 -1.07 0.20 0.04   The professor is going to use the z-scores to calculate the correlation coefficient between her scores and those of her TAs. To calculate the correlation coefficient, she sums the products of the z-scores. The professor should divide this sum by     .   The professor constructed a table of correlation coefficients between her scores and those of her TAs. Select the correct missing correlation.   Professor Teaching Assistant #1 Teaching Assistant #1      1 Teaching Assistant #2 0.37 0.91   Based on the correlation table, the professor should arrive at which of the following conclusions? The professor and both of her TAs are well calibrated.   The two TAs are well calibrated with each other but not with the professor.   The professor and TA #1 are well calibrated, but TA #2 is off.   The professor and TA #2 are well calibrated, but TA #1 is off.     The professor thinks she tends to be a harsh grader and decides to add 5 points to each student’s grade before converting the scores to z-scores and computing the Pearson correlation coefficient between her grades and the two teaching assistants’. This change in the professor’s scores will      the correlation between the professor’s scores and

The following table was generated from the sample data of 10 junior high students regarding the average number of hours they are unsupervised per night, the average number of hours they play video games per night, and their final grades in their math class. The dependent variable is the final grade, the first independent variable (x1) is the number of hours unsupervised each night, and the second independent variable (x2) is the number of hours of video games each night. Coefficients Standard Error t-Stat p-value Intercept 62.711817 4.607133 13.611896 0.000010 Hours Unsupervised 0.635048 0.915495 0.693666 0.513836 Hours Playing Video Games 7.528738 1.296727 5.805955 0.001145 Copy Data Step 1 of 2: Write the multiple regression equation for the computer output given. Round your answers to three decimal places. Answer 田 Tables 国 Keypad How to enter your answer (opens in new window) Keyboard Shortcuts X +

The following data represents the winning percentage (the number of wins out of 162 games in a season) as well as the teams Earned Run Average, or ERA.The ERA is a pitching statistic. The lower the ERA, the less runs an opponent will score per game. Smaller ERA's reflect (i) a good pitching staff and (ii) a good team defense. You are to investigate the relationship between a team's winning percentage - Y, and its Earned Run Average (ERA) - X. Winning Proportion - Y Earned Run Average (ERA) - X 0.623457 3.13 0.512346 3.97 0.635802 3.68 0.604938 3.92 0.518519 4.00 0.580247 4.12 0.413580 4.29 0.407407 4.62 0.462963 3.89 0.450617 5.20 0.487654 4.36 0.456790 4.91 0.574047 3.75 (b) Use R-Studio to find the least squares estimate of the linear model that expressed a teams winning percentage as a linear function of is ERA. Use four decimals in each of your answers.Y^i = ? + - Xi(e) A certain professional baseball team had an earned run average of 3.45 this past…

ANOVA. Dr. Milgramm is conducting a patient satisfaction survey, rating how well her patients like her on a scale of 1-10. Her patients tend to fall into three categories: “Like a lot”, “like somewhat”, and “dislike a lot”. She believes that she might get different satisfaction scores from people in each group, but (because she's not great at numbers) she wants you to do an ANOVA to be sure. She has collected data from 12 patients (three equal groups) with the following results.   Group 1) “Like a lot”               Mean:   8                    SS: 2   N:                    df:            Group 2) “Like somewhat”     Mean:   5                    SS: 6   N:                    df:             Group 3) “Dislike a lot”         Mean:    2                   SS: 4   N:                    df:              Grand Mean:          df Within-Group:__________ df Between-Groups:___________   Estimated Variance (S21) for Group 1: _______ Estimated Variance (S22) for Group 2: ___________ Estimated…

A researcher was interested in finding out whether students’ sense of belonging in a course differed between students attending classes on campus and students attending classes on Zoom. They recruited five students attending classes on campus and five students attending classes on Zoom to test this. Students were asked to complete a survey measuring how much they felt like they belonged in the course. The scale ranged from 0 (not at all) to 10 (very much). Students’ data, which were non-normal, are provided below. Campus Zoom 3 7 2 5 7 4 1 8 6 9   What is your obtained statistic?A) 19.5B) 35.5C) 3D) 10   What is your critical statistic?A) 17B) 19C) 0D) 1 What is your conclusion?A) Students taking the course on campus reported a significantly lower sense of belonging compared to students taking the course on Zoom.B) Students taking the course on campus reported a significantly higher sense of belonging compared to students taking the course on Zoom.C) Sense of belonging…

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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.

Auditors must make judgments about various aspects of an audit on the basis of their own direct experience, indirect experience, or a combination of the two. In a study, auditors were asked to make judgmentS about the frequency of errors to be found in an audit. The judgments by the auditors were then compared to the actual results. Suppose the following data were obtained from a similar study; lower scores indicate better judgments. If answer is zero enter "0". Direct Indirect Combination 18.0 17.8 15.6 17.8 19.2 16.3 14.0 17.0 21.4 20.2 19.1 24.3 19.1 20.3 24.5 24.8 20.9 27.0 26.7 25.0 23.9 Source Sum of Degrees Mean Square F p-value of Squares of (to 2 (to 2 (to 2 Variation (to 2 decimals) Freedom decimals) decimals) decimals) Treatments Error Total Use a = 0.05 to test to see whether the basis for the judgment affects the quality of the judgment. The p-value is - Select your answer - What is your conclusion? Select your answer -

(Please show all work on how you got this so I may learn from it and check my answers.) A researcher is interested in understanding if perfume affects how attractive a person is perceived tobe. To examine this phenomenon, the research randomly assigns the participants to rate theattractiveness of an individual from one of three groups: no perfume, a small amount of perfume, and alarge amount of perfume. Below are the ratings to how attractive the participants find the individual:NO Perfume      A SMALL Amount of Perfume             A LARGE Amount of Perfume4                        6                                                          05                        3                                                          13                        5                                                          05                        4                                                          14                        5                                                          23…

You are a manager for Company ABC and decide to compile data and analyze your employees’ level of satisifaction. You create a survey to ask each employee to rate their level of satisfaction working at Company ABC. Table 1 shows data of 15 people employees that responded to your survey. Each of the employees have the same job title: Sales Representative. The data set includes variables regarding an employee ID, gender, ethnicity, region, pay rate, employee satisfaction rating. Each employee was asked to rate their level of satisfaction working at Company ABC. A composite score from 0 (lowest) to 5 (highest) is shown as the data variable employee satisfaction. Table 1: Employee Data on 15 Sales Representatives at Company ABC