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- Mr. Acosta, a sociologist, is doing a study to see if there is a relationship between the age of a young adult (18 to 35 years old) and the type of movie preferred. A random sample of 93 adults revealed the following data. Test whether age and type of movie preferred are independent at the 0.05 level. Person's Age Movie 18-23 yr 24-29 yr 30-35 yr Row Total Drama 8 16 10 34 Science Fiction 10 8 12 30 Comedy 11 8 10 29 Column Total 29 32 32 93 (a) What is the level of significance?State the null and alternate hypotheses. H0: Age and movie preference are not independent.H1: Age and movie preference are independent.H0: Age and movie preference are independent.H1: Age and movie preference are independent. H0: Age and movie preference are not independent.H1: Age and movie preference are not independent.H0: Age and movie preference are independent.H1: Age and movie preference are not independent. (b) Find the value of the chi-square statistic for the sample. (Round…1. If there is a strong correlation between two variables X and Y, then X causes Y or Y causes X. O True O FalseOnly the question 5 and 6 need to be resolved. Others have been reaolved already. Question: sample of 15, 10 years old children was taken to study whether watching television reduces the amount of physical exercise, causing weight gains. The number of kilograms each child was overweight by was recorded (a negative number indicates the child is underweight). In addition, the number of hours of television viewing per week was also recorded. These data are listed in the table below. Television(hours) 42 34 25 35 37 38 31 33 19 29 38 28 29 36 18 Overweight (Kg) 8 3 0 0 6 6 3 3 -4 4 4 2 1 6 -3 Use an appropriate plot to investigate the relationship between Television(hours) and Overweight (KG). Briefly explain the selection of each variable on the X and Y axes and why? Calculate and interpret the coefficient of correlation (r) between Television(hours) and Overweight (KG).…
- 1) a.What is/are the appropriate measure(s) of central tendency for each of the variables in Columns B-F? Explain your answers in no more than two sentences each. b. Calculate the measures of central tendencies above c. Imagine that a 21st run is added to your dataset. See the table below for its data Run Eth. Gly. Acid. Temp pH 21 18.2 7.2 2.1 18 4.2 d. Do these data points change your choices of central tendency reported in Question 2b? Explain your answer. Attached dataset; a b c d e f Run Ethanol Glycerol Acidity Temp pH 1 4.8 3.5 0.84 24 3.8 2 9.6 7.3 0.27 24 3.8 3 10.2 7.2 0.27 24 3.8 4 8.5 5.1 0.55 24 3.8 5 7.3 3.2 0.68 24 3.1272 6 4.8 1.2 1.24 30 4.2 7 7.9 4.4 0.65 18 3.4 8 6.7 4.3 0.65 30 3.4 9 9.8 6.9 0.47 24 3.8 10 10.2 7.2 0.32 24 3.8 11 9.8 5.8 0.51 24 3.8 12 10.2 7.5 0.28 24 3.8 13 8.2 5.1 0.49 18 4.2 14 7.1 3.9 0.6 18 3.4 15 8.2 4.8 0.46 13.908 3.8 16 5.6 3.3…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.Mr. Acosta, a sociologist, is doing a study to see if there is a relationship between the age of a young adult (18 to 35 years old) and the type of movie preferred. A random sample of 93 adults revealed the following data. Test whether age and type of movie preferred are independent at the 0.05 level. Person's Age Movie 18-23 yr 24-29 yr 30-35 yr Row Total Drama 7 13 14 34 Science Fiction 11 11 8 30 Comedy 8 10 11 29 Column Total 26 34 33 93 (A) Find the value of the chi-square statistic for the sample. (Round the expected frequencies to at least three decimal places. Round the test statistic to three decimal places.)
- State the null hypothesis, Ho, and the alternative hypothesis, Ha, that would be used to test the following statements. (a) The linear correlation coefficient is positive. Ho: ? 0 Ha: ? 0 (b) There is no linear correlation. Ho: ? 0 Ha: ? 0 (c) There is evidence of negative correlation. Ho: ? 0 Ha: ? 0 (d) There is a positive linear relationship. Ho: ? 0 Ha: ? 0The phrase “Correlation does not equal causation” means: Question 30 options: there is no guarantee that a cause-and-effect relationship exists between two variables that are correlated. there is only a 30% chance that a cause-and-effect relationship exists between two variables. a cause-and-effect relationship only certainly exists when data are gathered in a specific way. a cause-and-effect relationship can only exist with ratio-level variables.If we reject the null hypothesis, H0: ρ = 0, what can we conclude about the population correlation coefficient? A) It is zero. B) It could be zero. C) It is not zero. D) It equals the computed sample correlation.
- If the null hypothesis is true in a test of the Pearson’s correlation between X and Y, then __________. a. higher scores of X are paired with higher scores of Y b. none of mentioned here c. higher scores of X are paired with low and high scores of Y d. higher scores of X are paired with lower scores of Y e. lower scores of X are paired with higher scores of YTwo computer companies are offering new software to universities. Let X and Y denote the number of software installed in three major universities by these two companies. Suppose that the variance of X is 583, the variance of Y is 752, and the covariance of X and Y is 179. a) Calculate the correlation coefficient (p) Select one: a. o.825 b. 0.270 c. 0.532 d. None of the answers1. Consider the following data set: -2 -1 0 1 4. 3 3 1 Calculate ở2, Var(Bo) Var(B,) and se(B), without using any statistical software.