A marketing research firm presented an advertisement for a product to random samples of potential customers inthree different regions of the country. The table below gives their reaction to the advertisement.REGIONIILiked576270Disliked312422Neutral121418The following is the R output:Pearson's Chi-squared testX-squared = 3.7043, df = *, p-value = 0.4475%3DIs there any evidence that the reaction to the advertisement is different for potential customers in the threeregions? (a = .05)The test problem ishedegree freedom isThe test statistic from the R output (keep 3 decimal points) isThe pvalue from the R output (keep 4 decimal points) isThe decision is

Solution-: We find the test of problem, degree of freedom, test statistic and p-value by using…

Answered: A marketing research firm presented an…

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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Four Air Force trainee pilots take a test of visual acuity (higher scores mean better acuity) and an anxiety test (higher scores mean more anxiety. The scores are as follows: Person Acuity (x) Anxiety (y) 1 1 7 2 1 8 3 2 4 4 4 -1 Calculate critical value , SP the correlation coefficient and determine whether the correlation is statistically significant at the .05 significance level, two-tailed
A physical therapist wanted to know whether the mean step pulse of men was less than the mean step pulse of women. She randomly selected 54 men and 70 women to participate in the study. Each subject was required to step up and down a 6-inch platform. The pulse of each subject was then recorded. The following results were obtained. Two sample T for Men vs Women N Mean StDev SE Mean Men Women 98% CI for mu Men - mu Women (- 12.20, - 1.00) T-Test mu Men = mu Women (vs H2 O C. Ho: H1 = H2; Ha: H1 #H2 (b) Identify the P-value and state the researcher's conclusion if the level of significance was a = 0.01. What is the P-value? P-value =
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a =0.01. Welght, x Varlablity in braking distance, y 5960 5390 6500 5100 5870 4800 2 1.75 1.95 1.93 1.57 1.64 1.50 E Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: P Vo Hạ: p Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical values are -to = and to = O B. The critical value is. Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? a significant linear correlation between vehicle weight and variability in braking distance on a dry surface. There Venough evidence…
In a sample of n=20 what would be the student's t test statistic for a correlation of r=0.400?
Á study was conducted that examined the relationship between alcohol consumption and risk of heart attack. In all, 417 men, age 40 or older, were tracked over ten years and the number of that experienced a heart attack was recorded. The participants were grouped by those who totally abstained from alcohol and those that drank moderately. For the results given in the table below, use the chi-squared test to find the p value for NHST at the .05 level. (In SPSS use the Yates continuity correction value.) Heart attack Alcohol Crosstabulation Count Alcohol Abstainer Moderate Total Heart attack No 197 192 389 Yes 9. 19 28 Total 206 211 417 Op= .090 Op= 121 !! Op=.067 Op = .048
A case-control (or retrospective) study was conducted to investigate a relationship between the colors of helmets worn by motorcycle drivers and whether they are injured or killed in a crash. Results are given in the accompanying table. Using a 0.05 significance level, test the claim that injuries are independent of helmet color. Color of Helmet Black White Yellow Red Blue Controls (not injured) 472 352 30 163 70 Cases (injured or killed) 201 106 8 67 34 Click here to view the chi-square distribution table. LOADING... Identify the null and alternative hypotheses. Choose the correct answer below. A. Upper H 0 : Whether a crash occurs and helmet color are independent Upper H 1 : Whether a crash occurs and helmet color are dependent B. Upper H 0 : Whether a crash occurs and helmet color are dependent Upper H 1 :…
The following information represents chlorine residuals in swimming pool (y) and the testing time (y) in different hours: n = 6, Ey = 8.8, Ey = 18.68, Ex = 42, Ex2 = 364, and Exy = 48.6 The sample correlation coefficient is: -0.6467 - 0.9899 - 0.9088 0.6467
(1) The following table summarizes the BMI collected for three different groups of a population. BMI N Mean SD Group A 100 21.6 2.1 Group B 100 24.8 1.8 Group C 100 27.9 1.3 Test the hypothesis whether there is a significant difference in the mean BMI scores among three groups. Use a = 0.05.
A sample of 25 individuals was taken to investigate the relationship between their annual income and number of years of education. The Pearson's correlation coefficient (r) was calculated to be 0.6. Test the hypothesis at a significance level of 0.01 that the population correlation coefficient is different from 0.
A researcher computes the correlation coefficient r= 0.4212 for an explanatory and response variable. What proportion of the changes in the response variables value is accounted for by the change in the explanatory variable's value? Give your answer to four decimal places.
Refer to the below table. Using an alpha = 0.05, test the claim that IQ scores are the same for children in three different blood lead level groups: low lead level, medium lead level, and high lead level). One-Way Analysis of Variance Summary Table for IQ Measurements for Children among Three Blood Lead Level Groups: Low Lead Level, Medium Lead Level, and High Lead Level. Source df SS MS F p Between-group (treatment) 2 469.1827 2677.864 2.30 0.104 Within-group (error) 118 203.6918 11745.05 Total 120
A study was conducted of 90 adult male patients following a new treatment for congestive heart failure. One of the variables measured on the patients was the increase in exercise capacity (in minutes) over a 4-week treatment The previous treatment regime had produced an average increase of μ = 2 minutes. The researchers wanted to evaluate whether the new treatment had increased the value of μ in comparison to the previous treatment. The sample data yielded ?̅ = 2.17 and ? = 1.05: Using α = 05, what conclusions can you draw about the research hypothesis?

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