f a random sample of size n = 20 from a normal population with the variance = 25 has the mean ī = 64.3, construct a 95% confidence interval for the population mean µ. %3D
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A: σ2=136.2s2=109.2α=0.01
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- Construct a 90% confidence interval for u, -la with the sample statistics for mean chalesterol content of a hamburger from two fast food chains and confidence interval construction formula below Assume the populations are approximately normal with unequal variances Stats X =71 mg. s, = 3.99 mg. n = 15 X2 = 59 mg. s2= 2.16 mg na Confidence interval when variances are not equal df is the smaller of n1 or n, - 1 Enter the andpoints of the intanial I Round to the nearest intoger as needed )Estimate the effects of each variable in the attached table in terms of a hazard ratio and provide 95% confidence intervals for each of the point estimatesLet x represent the number of mountain climbers killed each year. The long-term variance of x is approximately σ2 = 136.2. Suppose that for the past 11 years, the variance has been s2 = 116.2. Use a 1% level of significance to test the claim that the recent variance for number of mountain-climber deaths is less than 136.2. Find a 90% confidence interval for the population variance. A) Find the value of the chi-square statistic for the sample. (Round your answer to two decimal places.) B) Find or estimate the P-value of the sample test statistic. C) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis?
- In general, what is true about the relationship between the Sum of Squared Residuals in the restricted and unrestricted model? a. SSRr < SSRur b. SSRr > SSRur c. SSRr = SSRur d. SSRr = R-squared * SSRura) Compute the least-squares line for predicting y from 1/x. Round the answers to three decimal places. b) Using the better fitting line, find a 95% confidence interval for the mean value of y when x = 5.0. Round the answers to three decimal places. The 95% confidence interval for the mean value of y when x = 5.0 is?Tests the claim that #1 # p2. Assume the samples are normally distributed, random and independent. of = o} %3D s1 = 0.89 ; s2 = 0.92 I1 = 40.86 ; z2 = 40.58 n1 = 10; n2 = 17 a. Calculate the Standard Error si-i, = (use 3 decimals) b. Calculate the t-test statistic using the standard error from part a. t = (use 2 decimal places) c. What are the degrees of freedom? df = d. At a = 0.05 , Use the distribution table to find the critical values for the rejection region te = ± (use 4 decimal places) e. What is your conclusion? O Accept the alternative hypothesis and reject the claim O Accept the null hypothesis and support the claim O Fail to reject the null hypothesis and do not support the claim O Reject the null hypothesis and support the claim O Reject the alternative hypothesis and support the claim
- In a large design class, the scores on the "PDI" project were normally distributed with u = 100. The professor examined a sample of n= 56 students who used extra resources instead of only one resource like the other students in the class He found that the mean for students who used extra resources was M= 104.125. He used a one-sample t test to analyze the results, and part of the SPSS output is shown below. %3D One-Sample Statistics Std Error Mean N. Mean Std Deviation pdi 56 104.1250 12.58435 1 68165 One-Sample Test Test Value 100 95% Confidence Interval of the Difference Mean Difference df Sig (2-tailed) 55 Lower Upper 7.4951 pdi 2453 017 4.12500 7549 A. What are the professor's null and altemative hypotheses? B. 2. reject H, b. do not reject H, What is the professor's decision? C. resources. Identify this inform2tion and explain how you used it. You can use certain information from the table to answer Part B without referring to any otherI estimate a multiple linear regression model with two explanatory variables and 255 observations and I find that the RSS is 0.518514. The S.E of the regression is : Select one: a. the square root of the estimated variance of the estimator and it is 0.045361 b. the square root of the estimator of the errors variance and it is 0.045361 c. a measure of precision of the estimates and it is 0.037821 d. a measure of reliability of the estimated coefficients and it is 0.045361 e. the square root of the variance of the estimator and it is 0.0398126A manufacturer of hard safety hats for construction workers is concerned about the mean and the variation of the forces its helmets transmits to wearers when subjected to an external force. The manufacturer has designed the helmets so that the mean force transmitted by the helmets to the workers is 800 pounds (or less) with a standard deviation to be less than 40 pounds. Tests were run on a random sample of n = 40 helmets, and the sample mean and sample standard deviation were found to be 825 pounds and 48.5 pounds, respectively. Do the data provide sufficient evidence, at the a = 0.05 level, to conclude that the population standard deviation exceeds 40 pounds? What is the test statistic?
- WebAssign -→ xC OD Let x represent the number of mountain dimbers killed each year. The long term variance of x is approximately o= 136.2. Suppose that for the past 7 years, the vanance has been sE 110.6. Use a 1% level of significance to test the daim that the recent variance for number of mountain cimber deaths is less than 136.2., Find a 90% confidence interval for the population variance (a) What is the level of significance? State the null and alternate hypotheses. O Ho: a- 136.2; Hi o > 136.2 O Ho: - 136.2; Hạ o < 136.2 OHại o- 136.2; H o 136.2 O Hại a < 136.2; H o 136.2 (b) Find the value of the dhl-square statistic for the sample. (Round your answer to two decimal places.) What are the degrees of freedom? What assumptions are you making about the original distribution We assume a normal population distribution. We assume a binomial population distribution We assume a esponential population distribution We assume a uniform population distribution () Find or estimate the PyValue…Only answers for boththe value used in the equation for the t-test for independent means that approximates the sample size is known as the
