Assume you are a psychologist studying the relationship between chocolate consumption and happiness. You ask 10 participants to rate how much chocolate (in ounces) they ate in the last week, and how happy they felt throughout the week on the average, on a scale ranging from 1 (extremely unhappy) to 10 (extremely happy). You hypothesize that there is some relationship between chocolate consumption and happiness. Here are their scores:| Participant # | Chocolate eaten during week (oz) | Happiness rating ||---------------|-----------------------------------|------------------|| 1 | 5 | 3 || 2 | 6 | 9 || 3 | 3 | 7 || 4 | 7 | 6 || 5 | 4 | 4 || 6 | 6 | 8 |This data could be used to analyze whether there is a correlation between chocolate intake and reported happiness levels. The image displays a table with two columns of numbers, followed by a multiple-choice question about statistical hypotheses.Data Table:- Column 1: 7, 8, 9, 10- Column 2: 10, 6, 2, 1Multiple-Choice Question:"Which of the following are the correct statements of the null and alternative hypotheses, H₀ and Hₐ, where ρ is 'rho', the population correlation coefficient between X and Y?"Options:- ○ H₀: ρ = 0 and Hₐ: ρ ≠ 0- ○ H₀: ρ ≠ +1.0 and Hₐ: ρ = +1.0- ○ H₀: ρ > 0 and Hₐ: ρ ≤ 0- ○ H₀: ρ ≤ 0 and Hₐ: ρ > 0- ○ H₀: ρ ≠ 0 and Hₐ: ρ = 0There are no graphs or diagrams included.

It is given that the data of chocolate consumption and happiness.

Answered: Which of the following are the correct…

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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The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. 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. Should we expect that there would be a correlation? Use a significance level of a = 0.01. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. O A. OB. Best Actor (years) 70- 20- 20 70 Best Actress (years) Best Actor (years) The linear correlation coefficient is r= (Round to three decimal places as needed.) xample Get more help. 70- ||||||||| THHHH 20+ 20 Best Actr 11111 H ||||||||| Qu 70 Q *** Best Actor (years) C. 20+ 20 P +||||| HHHH 70 Best Actresses and Best Actors 29 Best Actress 29 30 29 59 32 32 43 Best Actor 45 37 40 43 49 50 59 48 O D. Best Actor (years) 64 37 70- 20+ 20 D M 23 42 53 55 43…
In a sample of n=20 what would be the student's t test statistic for a correlation of r=0.400?
O REGRESSION AND CORRELATION Linear relationship and the sample correlation coefficient Shas Below are four bivariate data sets and the scatter plot for each. (Note that each scatter plot is displayed on the same scale.) Each data set is made up of sample values drawn from a population. y 11 10- 94 S- 1.0 6.7 1.0 7.4 10- 2.0 9.4 2.0 9.1 3.0 4.0 3.0 7.0 4.0 9.1 6+ 4.0 5.3 5- 5.0 4.7 5.0 8.0 4. 3 2- 7.0 6.4 6.0 1.7 6.0 5.1 7.0 | 4.6 8.0 10.1 9.0 5.1 8.0 6.5 9.0 5.7 10.0 3.7 10.0 8.0 | Figure 1 Figure 2 t 1.0 3.2 1.0 1.0 2.0 2.0 2.0 4.2 3.0 3.3 3.0 3.0 4.0 4.9 4.0 4.0 5.0 4.5 5.0 5.0 6.0 6.8 6.0 6.0 7.0 5.8 7.0 7.0 8.0 7.3 8.0 8.0 9.0 6.6 9.0 9.0 10.0 8.2 Figure 3 10.0 10.0 Figure 4 Explanation Check e 2021 McGraw-H Education. All Rights Reserved. Terms of Use I Privacy Accessibilty P Type here to search
Which of the following is the correct decision and conclusion based on the result? a. Decision: Fail to reject the null hypothesis Conclusion: There is a significant correlation between the variables. Thus, as COVID cases increases, the day also increases. b. Decision: Reject the null hypothesis Conclusion: There is a significant correlation between the variables. Thus, as the day goes by, daily COVID cases increases. c. Decision: Reject the null hypothesis Conclusion: There is no significant correlation between the variables. Thus, as the day goes by, daily COVID cases decreases. d. Decision: Fail to reject the null hypothesis Conclusion: There is no significant correlation between the variables. Thus, as the day goes by, daily COVID cases will be the same.
If the linear association between two numerical variables is studied and the correlation coefficient is 0.32, it can be concluded that:a. The relationship between the variables is inverse and weak. b. The percentage of variability observed in the data that is explained by the error is 89.76%. c. The percentage of observed variability in the data that is explained by the model is 32%. d. None is correct Please explain clearly, thank you
Suppose data is obtained from 20 pairs of (x, y) and the sample correlation coefficient is 0.80. (a) Test the hypothesis that Ho: p = 0 against H₁ :p #0 with a = 0.01. Reject the null hypothesis. (b) Test the hypothesis that Ho: p = 0.25 against H₁: p = 0.25 with a = 0.01. Reject the null hypothesis. (c) Construct a 99% two-sided confidence interval for the correlation coefficient. Round your answer to 3 decimal places. < p < i i
will this be sufficient or is not sufficient evidence.
18
Which of the following is not a cause of perfect multicollinearity? Select all that apply. One of the explanatory variables is equal to half of another explanatory variable for 100% of the observations in the sample. The correlation between two of the explanatory variables is 1.00. One of the explanatory variables is equal to half of another explanatory variable for 20% of the observations in the sample. A dummy variable for male is included at the same time as a dummy variable for non-male. One of the regressors is X and another regressor is X².
Are there ever any circumstances when a correlation such as Pearson’s r can be interpreted as evidence for a casual connection between two variables? If yes, what circumstances?
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Which of the following are the correct statements of the null and alternative hypotheses, Ho and HA, where p is "rho", the population correlation coefficient between X and Y? HO: p = 0 and HA: p = 0 HO: p +1.0 and HA: p = +1.0 HO:p> 0 and HA: p ≤ 0 HO: p = 0 and HA: p > 0 HO: p= 0 and HA: p = 0.