ontParagraphStyles4.The given table below shows the respective correlation coefficients between twovariables with the corresponding p-values. Assume that the target population iscomposed of all ADZU employees.Required:a) Write the null hypothesis(Ho) and alternative hypothesis (Ha) for eachpair of variables as reflected in the table below.b) Decide whether the null hypothesis can be rejected and then discuss theresults (at least 15 words) for each pair of variables.Fasting Blood Sugar Level(FBSL)Systolic Blood Pressure (SBP)0.85p-value = 0.03Body Mass Index (BMI)-0.63p-value=0.005FocusWAccessibility: Investigate171743

Given that: ρ1=0.85 p1 = 0.03 ρ2=0.63 p2 = 0.005

Answered: 4. The given table below shows the…

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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For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.022. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is %, which is so there sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)
Online clothes An online clothing retailer keeps trackof its customers’ purchases. For those customers who signed up for the company’s credit card, the com-pany also has information on the customer’s Age and Income. A random sample of 500 of these customers shows the following scatterplot of Total Yearly Pur-chases by Age:The correlation between Total Yearly Purchases and Age isr = 0.037. Summary statistics for the two variables are: a) What is the linear regression equation for predictingTotal Yearly Purchase from Age?b) Do the assumptions and conditions for regressionappear to be met?c) What is the predicted average Total Yearly Purchasefor an 18-year-old? For a 50-year-old? d) What percent of the variability in Total Yearly Pur-chases is accounted for by this model? e) Do you think the regression might be a useful one forthe company? Explain.
19. The director of an alumni association for a small college wants to determine whether there is any type of relationship between the amount of an alumnus’s contribution (in dollars) and the years the alumnus has been out of school. The data follow. Years x | 1 5 3 10 7 6 Contribution y | 500 100 300 50 75 80 a) Plot the scatter diagram for the paired data. b) Assuming a 5% level of significance, use hypothesis testing and the linear correlation coefficient (r) to determine if there is a linear correlation. ( c) Find the equation of the regression line and plot it on your scatter diagram using an x of 3 and an x of 10. d) Determine the residual value for an x of 5 and explain its meaning.
The accompanying table gives amounts of arsenic in samples of brown rice from three different states. The amounts are in micrograms of arsenic and all samples have the same serving size. The data are from the Food and Drug Administration. Use a 0.05 significance level to test the claim that the three samples are from populations with the same mean. Do the amounts of arsenic appear to be different in the different states? Given that the amounts of arsenic in the samples from Texas have the highest mean, can we conclude that brown rice from Texas poses the greatest health problem? Click the icon to view the data. What are the hypotheses for this test? O A. Ho: At least one of the means is different from the others H₁ H₁ H₂ H3 OB. Ho: H₁ H₂=H3 H₁: At least one of the means is different from the others OC. Ho: H₁ H₂=H3 H₁: H₁ H₂ #H3 O D. Ho: M₁ #₂ #H3 H₁: H₁ H₂=H3 Determine the test statistic. The test statistic is (Round to two decimal places as needed.) Determine the P-value. The P-value…
even though we may observe a strong relationship between the explanatory and response variables, a lurking variable may also influence the response vatiabke. This is reffered to as A. correlation B. confounding C.association D. causation
An Economics instructor assigns a class to investigate factors associated with the gross domestic product (GDP) of nations. Each student examines a different factor (such as life expectancy, literacy rate, etc.) for a few countries and reports to the class. Apparently, some of the classmates do not understand Statistics very well because several of their conclusions are incorrect. Explain the mistakes in comments a and b below. a) Explain the mistake in the statement "There was a very strong correlation of 1.22 between Life Expectancy and GDP" Choose the correct answer below O A. A correlation cannot be greater than 1. O B. A correlation that is greater than 1 implies that the variables are not quantitative, so the correlation cannot be interpreted. OC. A correlation that is close to 1 implies a very weak correlation. The correlation must be close to 10 for it to be interpreted as a very strong correlation. O D. A correlation that is greater than 1 implies a weak correlation, not a…
8) The following results are from data that were collected from the various high schools around the county. The dependent variable is % OF STUDENTS GOING TO COLLEGE, and the independent variables are: AVERAGE CLASS SIZE, COMBINED SAT SCORES, SPENDING PER STUDENT, AVERAGE TEACHER SALARY, AND % TAKING THE SAT Since the 3 variables AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are each not significant at the 10% level of significance individually, in order to test to see if as a group they are significant the 3 variables are excluded and another regression is run. The results are as follows: a) At the 10% level of significance, test whether as a group AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are significant. Be sure to state the null and alternative hypotheses for this hypothesis test.
When analyzing an association between two variables, the size of the correlation may be deceptive because of a.) a spurious association b.) range restriction c.) conflated data d.) poor statistical validity
A sample contains 61 pairs of values. Find the critical value for the linear correlation coefficient from Table A-6 corresponding to a 0.05 significance level. A. 0.330 B. 0.236 C. 0.279 D. 0.254 ( don't hand writing solution)
Dr. Morgendorffer wants to develop a questionnaire that measures employees' burnout. But during her literature review, she learns that burnout is a variable with three separate dimensions: exhaustion, cynicism, and detachment. Which of the following checks will help ensure that Dr. Morgendorffer's burnout questionnaire is valid? O a. Ensuring that the items across all three dimensions are correlated with each other O b. Ensuring that there is a high level of stability for each of the three dimensions OC. Ensuring that the dimensions represent parallel forms of the questionnaire O d. Ensuring that all three dimensions have been adequately represented in the questionnaire
Five observations taken for two variables follow. xi 6 11 15 21 27 yi 6 9 5 18 12 a. compute the sample covarinace b. Compute the sample correlation coefficient. (Round your answer to three decimal places.)
6.50 How's it going?: The American National Election Studies (ANES) collects data on voter attitudes and intentions as well as demographic information. In this question we will focus on two variables from the ANES dataset (ANES, 2012). region (levels: Northeast, North Central, South, and West) whether the respondent feels things in this country are generally going in the right direction or things have pretty seriously gotten off on the wrong track To keep calculations simple we will work with a random sample of 500 respondents from the ANES dataset. The distribution of responses are as folows: Right Direction Wrong Track Total Northeast 29 54 83 North Central 44 77 121 South 62 131 193 West 36 67 103 Total 171 329 500 There are TWO parts to this question. One is a Chi-Squared GOF and one is a Chi-Squared Test for Independence. Think about the differences between the two tests to determine which one to use on which part.a) Region: According to the 2010 Census, 18%…

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