= Conclusion:Fail to reject the null hypothesis; there is no significant relationship between gender and willingness to seek mental health assistance. Fail to reject the null hypothesis; there is a significant relationship between gender and willingness to seek mental health assistance. Reject the null hypothesis; there is no significant relationship between gender and willingness to seek mental health assistance. Reject the null hypothesis; there is a significant relationship between gender and willingness to seek mental health assistance. Compute Cramér’s V to measure the size of the effect.Cramér’s V = Research has demonstrated strong gender differences in teenagers' approaches to dealing with mental health issues (Chandra & Minkovitz, 2006). In atypical study, eighth-grade students are asked to report their willingness to use mental health services in the event they were experiencing emotionalor other mental health problems. Typical data for a sample of n = 150 students are shown in the following table.A-ZWillingness to Use Mental Health ServicesProbably NoMaybeProbably YesMales17321160Females13433490307545n = 150Do the data show a significant relationship between gender and willingness to seek mental health assistance? Test with a = .05.bongoChi-Square DistributionDegrees of Freedom = 160 1 2 3AAN4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30x2 x2-criticalx2bongoConclusion:Fail to reject the null hypothesis; there is no significant relationship between gender and willingness to seek mental health assistance.Fail to reject the null hypothesis; there is a significant relationship between gender and willingness to seek mental health assistance.Reject the null hypothesis; there is no significant relationship between gender and willingness to seek mental health assistance.Reject the null hypothesis; there is a significant relationship between gender and willingness to seek mental health assistance.Compute Cramér's V to measure the size of the effect.Cramér's V =Save & ContinueContinue without savingII

Introduction: The factor gender has 2 levels, Males and Females, and the factor “Willingness to Use…

Answered: x²-critical Conclusion: Fail to reject…

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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1. Calculate r2 2. Interpret r2 in the context of this research. How large is this effect (small, medium, large)? 3. Make an statistical decision about the null using alpha =.05. Will you reject or retain the null based on your data? 4. Provide a conclusion of the data using Descriptive statistics and the context of the research.
Identify the conclusion for this hypothesis test. O A. Fail to reject Hn. There is not sufficient evidence to warrant support of the claim that more than 20% of users develop nausea. B. Fail to reject Ho- There is sufficient evidence to warrant support of the claim that more than 20% of users develop nausea. C. Reject Hg. There is sufficient evidence to warrant support of the claim that more than 20% of users develop nausea. O D. Reject Ho. There is not sufficient evidence to warrant support of the claim that more than 20% of users develop nausea.
Medical research has shown that repeated wrist extensions beyond 20 degrees increase the risk of wrist and hand injuries. Each of 24 students at a university used a proposed new computer mouse design, and while using the mouse, each student's wrist extension was recorded. Data consistent with summary values given in a paper are given here. 27 22 29 24 27 27 25 25 24 24 24 25 28 25 24 28 27 26 31 25 28 27 27 25 USE SALT (a) Use these data to estimate the mean wrist extension for people using this new mouse design using a 90% confidence interval. (Round your answers to three decimal places.)
(a) Write the claim mathematically and identify H0 and Ha. (b) Find the standardized test statistic z, and its corresponding area. (c) Find the P-value. (d) Decide whether to reject or fail to reject the null hypothesis. (e) Interpret your decision in the context of the original claim.
Suppose we are making predictions of the dependent variable y for specific values of the independent variable x using a simple linear regression model holding the confidence level constant. Let Width (C.I) = the width of the confidence interval for the average value y for a given value of x, and Width (P.I) = the width of the prediction interval for a single value y for a given value of x. Which of the following statements is true? Width (C.I) = 0.5 Width (P.I) Width (C.I) = Width (P.I) Width (C.I) > Width (P.I) Width (C.I) < Width (P.I)
4. Which of the following is used in model fit comparisons? A. Alkaike Information Criterion test B. The R-squared adjusted C. The Bayesian Information Criterion D. All of the above 5. Dr. Musantu conducted an estimation between y (dependent variable) and x (independent variable) in Stata. He obtained 0.332 coefficient of x and standard error of 0.021. What is the value of the t-statistic? A. 14.809 01392 B. 15.809 C. 16.809 D. None of the above 6. Is the above regressor (in question 8) significant at 5% (which gives 1.96 critical values) level of significance? A. No B. Yes 7. In a log-log regression model, what does the slope coefficient measure? A. The elasticity or percentage change of y with respect to a percentage change in x. B. The change in y which the model predicts for a unit change in x. C. The change in x which the model predicts for a unit change in y. D. 100 multiplied by the ratio y/x. 0.021
Medical research has shown that repeated wrist extensions beyond 20 degrees increase the risk of wrist and hand injuries. Each of 24 students at a university used a proposed new computer mouse design, and while using the mouse, each student's wrist extension was recorded. Data consistent with summary values given in a paper are given here. 27 27 23 26 27 25 25 24 22 25 24 28 27 26 31 25 USE SALT 24 24 25 28 28 27 27 25 (a) Use these data to estimate the mean wrist extension for people using this new mouse design using a 90% confidence interval. (Round your answers to three decimal places.) 25.148 26.518 ]× )
A sociologist wishes to study whether the rank attained by officers in the New York City Police Department (NYPD) is related to gender. Data have been collected for both male and female officers in NYPD. The summary data and test for independence results from StatCrunch are given below. At a= 0.05 level of significance, draw a conclusion about whether these data indicate that the rank of the officer is independent of gender.(a) Is this an observational study or experiment?(b) What are the explanatory and response variables, respectively?Explanatory variable:Response variable:(c) Write down the null and alternative hypotheses of the test for independence.Contingency table results:Rows: RANKColumns: GENDER male female total officer 21900 4281 26181 detective 4058 806 4864 sergeant 3898 415 4313 lieutenant 1333 89 1422 captain 359 12 371 higher ranks 218 10 228 total 31766 5613 37379
The dataset below that contains information on fuel efficiency (in miles/gallon) from random samples of cars with manual and automatic transmissions as well as cars with other transmissions. Do these data provide strong evidence of a difference between the average fuel efficiency of cars with manual and automatic transmissions in terms of their average citymileage? 1. Set up the null and alternative hypotheses.2. Compute the test statistic.3. State the p-value for the test. State the decision and conclusion of the test in context. Feel free to use excel, Rstudio, or any other methods to answer the Question! Thanks Auto Manual 77 22 126 30 52 28 62 26 62 29 106 20 27 27 28 22 24 26 26 26 30 26 21 23 21 28 23 29 25 25 20 25 20 22 18 17 17 27 14 25 15 19 18 27 17 30 14 23 18 24 17 23 14 22 15 23 18 24 17 27 14 23 19 22 17 25 17 19 14 26 16 21 16 23 14 18 17 18 17 18 14 18 16 19 16 19 14 21 18 18…
3)A paper reported that a simple linear regression model was built based on 24 samples. The 95% confidence interval for the slope was (3.3, 9.1). a)What is thet statistic for the slope? b)What is the 99% confidence interval for the slope? c)Is the model significant at 1% significance? d)What is the R2 for the model?
The total expenses of a hospital (dependent variable) are related to many factors. One of these factors is the number of admissions to the hospital (independent variable). Using the summary output below to answer, what is the meaning (analysis) of the coefficient of determination? SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Statistics Regression Residual Total df 0.98706 0.974288 0.972145 8.106794 Coefficients 14 1 12 13 SS 29883.07 788.6412 30671.71 Standard Error Intercept 1.518053 Admissions 0.668591 OA) is the value of Expenses with one unit increase in Admissions 3.248929 0.031354 MS 29883.07 65.7201 t Stat 0.467247 21.32375 F 454.7022 P-value 0.648693 6.59E-11 Significance F 6.59E-11 Lower 95% -5.56075 0.600276 Upper 95% 8.59686 0.736907
Physical properties of six flame-retardant fabric samples were investigated in an article. Use the accompanying data and a 0.05 significance level to determine whether a linear relationship exists between stiffness x (mg-cm) and thickness y (mm). O Ho: P = 0 H₂: P = 0 O Ho: P = 0 H₂:p>0 State the appropriate null and alternative hypotheses. O Ho: P = 0 Ha: P < 0 O Ho: P = 0 Ha: P = 0 X y r = 7.95 24.63 12.39 7.06 24.17 35.70 0.25 0.64 0.32 0.27 0.80 0.56 Compute the value of the sample correlation coefficient, r. Round your answer to four decimal places. Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.) t = P-value = State the conclusion in the problem context. O Fail to reject Ho. The data does not indicate that the population correlation coefficient differs from 0. O Reject Ho. The data indicates that the population correlation coefficient differs from 0. O Reject Ho. The data does not…

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	=	Conclusion: Fail to reject the null hypothesis; there is no significant relationship between gender and willingness to seek mental health assistance. Fail to reject the null hypothesis; there is a significant relationship between gender and willingness to seek mental health assistance. Reject the null hypothesis; there is no significant relationship between gender and willingness to seek mental health assistance. Reject the null hypothesis; there is a significant relationship between gender and willingness to seek mental health assistance. Compute Cramér’s V to measure the size of the effect. Cramér’s V =