Use the Pearson r correlation table to answer questions about the relations between table variables (symbols: * p < .05, ** p < .01, *** p < .001). variable contacts demeanor preparation contacts 1 -0.139 -0.004 demeanor -0.139 1 0.886*** preparation -0.004 0.886*** 1

Use the Pearson r correlation table to answer questions about the relations between table variables (symbols: * p < .05, p < .01, * p < .001). variable contacts demeanor preparation contacts 1 -0.139 -0.004 demeanor -0.139 1 0.886* preparation -0.004 0.886* 1

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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variable	contacts	demeanor	preparation
contacts	1	-0.139	-0.004
demeanor	-0.139	1	0.886***
preparation	-0.004	0.886***	1

Similar questions

2. A researcher performed a Pearson correlation analysis on the variables anxiety, wellbeing and stress to identify if they were correlated. The researcher performed the analysis in Jamovi and obtained the below table. Report the results of this analysis. Correlation Anxiety Wellbeing Stress Anxiety Pearson's r p-value Wellbeing Pearson's r -0.19 p-value 0.060 99 Stress Pearson's r 0.75 0.04 p-value < .001 0.720 N 99 99 |||
Hi! I really need help interpreting the results of this correlation matrix. Please help me answer these questions. Thanks! What were the results of your analysis in narrative form? Be clear about whether or not a significant relationship was indicated and the strength and nature of that relationship. How do you write out the numerical results of your analysis in APA format?
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The ages of the runners in a race and their finishing positions are given in the following table. Assuming x is the finish position and y is the person's age, is there a significant correlation between age and finishing position? Answer Choices Not significant Not one of these Significant at both 5% and 1% Significant at 5% but not 1% Significant at 1%
The following table shows the weekly sales, test scores & achievement ratings of 5 salespersons working for a local car dealership: Salesperson Weekly Sales (Y) Sales Aptitude Test Score (x1) Mechanical Achievement (x2) Walters 11 10 6 Sullivan 5 4 2 Obmer 8 1 4 Smith 12 7 5 Jones 4 3 1 Brown 6 5 3 Black 7 2 2 Calculate the multiple correlation coefficient.. Select one: a. 0.925 b. 0.952 c. 0.295 d. 0.592
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OA. Tip Amount ($) Construct a scatterplot. Choose the correct graph below. 25- The table below includes data from taxi rides. The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars. Is there sufficient evidence to conclude that there is a linear correlation between the time of the ride and the tip amount? Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a 0.01. Does it appear that riders base their tips on the time of the ride? Click here for information on the taxi rides. 0 35 Ride time (minutes) Determine the linear correlation coefficient. The linear correlation coefficient is r= (Round to three decimal places as needed.) Tip Amount ($) B. Q 25- Q 0- 0 35 Ride time (minutes) Tip Amount ($) C. 25- Q 0 35 G Ride time (minutes) O D.…
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The following data refers to the amount of caffeine (in mg) consumed by ten university students and their time to complete a practice test (in minutes) for a Economics Exam. Use attached Graph and Table to answer question below pls Describe the overall pattern of the relationship between caffeine amount and time to finish the practice exam in graph diagram provided. Does it follow a straight-line pattern? Is there a positive or negative association, or neither? How strong is the relationship?
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. Differentiate between correlation vs. causation. When two variables are correlated (such as strength and running speed), they are associated with one another. Explain how, even if there is a correlation between the two, one might not cause the other. Provide an example of an association between variables where a causal relationship makes sense conceptually. Why can't correlations be used as a tool to prove a causal relationship between variables rather than just an association?