Exercise #1: n = 30 observations X Y 52 62 47 68 38 17 བdཆེར Y X Y 43 43 44 46 ཆེར 79 81 39 43 47 86 69 78 55 52 57 60 44 46 38 68 71 91 52 55 50 54 67 62 66 80 63 65 47 52 68 78 70 71 45 56 42 16 28 72 62 47 41 64 70 69 71 68 78 37 55 1. Compute the value of the sample correlation between variables X & Y; denoted by r Note: r = SXY √√Sxx x Syy 2. Test - Use Excel to compute these S's like I have done in previous homework assignments HA: (μx μy) 0 at α = 5% using the p value Method a. Assuming independent populations (i.e., disregarding the correlation) b. Using Match Pairs Technique
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- D.1.2 Test the hypothesis that the average content of containers of a particular lubricant is 10 liters if the contents of a random sample of 10 containers are 10.2, 9.7, 10.1, 10.3, 10.1, 9.8, 9.9, 10.4, 10.13, and 9.8 liters. Use α 0.01 level of significance and assume that the distribution of contents is normal.Suppose a linear model y=β0+β1xy=β0+β1x is fit to a sample data set, and a test of the null hypothesis H0:β1=0H0:β1=0 against an alternative hypothesis HA:β1≠0HA:β1≠0 is performed; a PP-value of 0.4203 is obtained. Which of the following scatter plots depicts the data set on which this model was fit and the hypothesis test was performed?A snack food manufacturer estimates that the variance of the number of grams of carbohydrates in servings of its tortilla chips is 1.33. A dietician is asked to test this claim and finds that a random sample of 24 servings has a variance of 1.37. At α=0.01, is there enough evidence to reject the manufacturer's claim? Assume the population is normally distributed. Complete parts (a) through (e) below. (a) Write the claim mathematically and identify H0 and Ha. A. H0: σ2≤1.33 (Claim) Ha: σ2>1.33 B. H0: σ2≠1.33 Ha: σ2=1.33 (Claim) C. H0: σ2≥1.33 Ha: σ2<1.33 (Claim) D. H0: σ2=1.33 (Claim) Ha: σ2≠1.33 (b) Find the critical value(s) and identify the rejection region(s). The critical value(s) is(are) enter your response here. (Round to two decimal places as needed. Use a comma to separate answers as needed.) Choose the correct statement below and fill in the corresponding answer boxes. A. The…
- 16. For the data shown to the right, determine the linear correlation coefficient using the formulas shown below. Compare your answers in part (a) and (b). x 4 5 1 0 0 y 6 7 0 0 −4 a. Use the definition r=1n−1∑xi−xyi−ysxsy.For each of the following studies: (a) identify the sample size(s), (b) state if we have a significant difference based on the calculated t-value given at alpha = .05 and alpha = .01. In the two-sample case, assume equal sample sizes, and (c) calculate r2 if significant. One-sample t test: t(30) = 2.050 Two sample independent measures t-test: t(18) = 1.50 One-sample t-test: t(35) = 1.75Here is a bivariate data set.xy182425915011737106295223812246 Find the correlation coefficient and report it accurate to four decimal places. r =
- 1. A) In a regression analysis, if SSE = 900 and SSR = 300, find the coefficient of determination. a)0.250 b) 0.500 c) 0.750 d) 0.900 B) In a regression analysis, if SST = 4,500 and SSR = 2,565, then the correlation coefficient could be a) 0.43 or −0.43. b) 0.57 or −0.57. c) 0.755 or −0.755. d) 1. C) If the coefficient of determination is 0.60, find the percentage of variation in the dependent variable explained by the variation in the independent variable. a) 0.60% b) 0.7746% c) 60% d) 77.46%Two samples of sizes 60 and 90 have 52 and 48 as the respective A.Ms. and 9 and 12 as the respective S.Ds. Find the A.M and S.D. of the combined sample of size 150.2- An expert estimates that the distribution parameter for durability times of parts produced with machine A in the factory is different from the distribution parameter for durability times of parts produced with machine B. Durability times of 4 parts produced from machine A and 4 parts produced from machine B are given below. Find the Mann-Whitney U value by using these data. a) 18 B) 6 NS) 16 D) 20 TO) 12
- You obtained the following raw data when setting up a Biuret standard curve: BSA (mg/ml) Absorbancy 540nm 0 0.158 1 0.210 2 0.260 3 0.305 4 0.360 5 0.410 6 0.455 7 0.510 8 0.530 9 0.550 10 0.554 What would the quality of the line-fit (R2 value) be if you do not exclude experimental outliers? (Give you answer to 4 decimal places)given normally distributed sample x=12 and s=3, use the Empirical Rule determine the upper and lower bounds to contain approximately 95% of your dataA)I will test the claim that there is no correlation (start with the Claim and finish with the conclusion) The best estimate The P value is (big/small) so I have to (either give the average of the y's or plug in the x into the y-=mx+b)