1. A n = 5 data points given in table (r is the predictor variable and y is the response variable).x y1223451-11a--1-2Answer the following questions by hand calculation. Show your every detail of calculation!. Then verify your answers using theR-output in figure 1.1(e) Find 90% confidence interval (CI) and prediction interval (PI) of ŷ when r = 2. Hint: Useformulas in Slide 29-32.

Answered: Image /qna-images/answer/b0829f39-3342-4089-9862-837e44539dc3.jpg

Answered: 1. A n = 5 data points given in table…

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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Based from the photo, This is the step1, so step 2 and step 3 and Step 4 must be answered. (Step 2: Test Statistic -Pearson's r correlation coefficient AND Step 3: Critical Values, and Step 4: Solve For the test stat) so based it from the photo. The table shows the number of hours spend by 30 students in studing and their test scores. Solve for the Pearson’s r and interpret the results. Use 5% significance level. Step 1: Null and Alternative Hypothesis Ho: r = 0; There is no significant relationship between the number of hours spent studying and the students test scores. Ha: r ≠ 0; There is a significant relationship between the number of hours spent studying and the students test scores. Step 2: Test Statistic -Pearson's r correlation coefficient Step 3: Critical Values, Step 4: Solve For the test stat PLEASE SHOW ME COMPLETE SOLUTIONS AND CORRECT ANSWERS THANK YOU!! It was a pleasure to me. HIGHLIGHT STEP 4: (step 4 is must)!!
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5. The National Center for Health Statistics published data on heights and weights. We obtained the following data from 10 randomly selected males 8-12 years of age. * y Height 69 Weight 151 72 154 70 160 200 Weight go IGO Regression Equation: Correlation r = 67 153 140 (20 O 75 201 66 126 a. If the researcher uses "Height" to predict "Weight" then the response variable is weight b. Use your calculator to create a scatter plot. Copy the scatter plot below (draw it). Make sure to label the horizontal axis and vertical axis, and provide the minimum and maximum values (displayed on your graph on your calculator) on each axis.. 70 174 71 185 60 70 Height 80 c. Is the association between the two variables positive or negative, or no association? (circle one) 68 143 g. Identify the slope of the regression line: and mention both men's heights and weights.)" d. Use your calculator to find the regression line (or line of best fit) and the correlation r. (Make sure something has a hat on it.) 65…
#6
5. You have a sample of 19 students and plan to determine if a linear relationship can be used to predict the SAT score as a function of the high school GPA. What value does the correlation coefficient need to exceed, according to the r√n> 3 rule, in order for you to be able to say that the correlation between the SAT score and the high school GPA is significant, instead of it having occurred by random chance? Write your answer as a decimal correctly rounded to three decimal places.
Only solve 18 question
Solve the problem. An article in a journal examined the attitudes of three groups of professionals on the condition of the environment, and quantified their responses on a seven-point scale (1= no problem to 7 = disaster very likely). The mean scores for the groups are: A: 4.90 , B: 4.55 , and C: 4.51 . Using an experimentalwise error rate of a = .05, Tukey's minimum significance for comparing means is 0.29. Use this information to conduct a multiple comparisons of the means. O The lowest mean differs significantly from the other two, but there is no significant difference in the other two means. O All means are significantly different. O The highest mean differs significantly from the other two, but there is no significant difference in the other two means. O There is no significant difference in any of the means.
Please let me know if I calculated relative risk correctly. Thank you for your assistance.
Q2. A fast-food chain decided to carry out an experiment to assess the influence of advertising expenditure on sales. Different relative changes in advertising expenditure, compared to the previous year, were made in eight regions of the country, and resulting changes in sales levels were observed the accompanying table shows the results. Increase in advertising expenditure (%) 0 5 15 20 25 30 35 40 Increase in sales (%) 5 10 18 25 35 50 60 65 Determine the value of ∑X, ∑X2, ∑Y, ∑Y2, ∑XY. Where X represent independent variable and Y for dependent variable. [2] Determine and interpret the coefficient of correlation between the two variables. [1] Determine the value of regressions coefficients and write down the simple linear regression
1. A dietetics student wanted to look at the relationship between calcium intake and knowledge about calcium in sports science students. Table 1 shows the data she collected. Knowledge Respond ent Calcium intake Respond ent Knowledge Calcium intake score score (Out of 50) number (mg/day) number (Out of 50) (mg/day) 1 10 450 11 38 940 2 42 1050 12 25 733 3 38 900 13 48 985 4 15 525 14 28 763 5 22 710 15 22 583 6 32 854 16 45 850 7 40 800 17 18 798 8 14 493 18 24 754 9 26 730 19 30 805 10 32 894 20 43 1085 Is there a relationship between calcium intake and knowledge about calcium in sports science students?
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Here are the world record race times for women in the 10,000-meter run over several years. a) Which is the explanatory variable and which is the response variable? Year Race Time (seconds) 1967 2286.4 b) Make a scatterplot of these data. You do not have to draw the scatterplot for me. Describe what you see (form, direction, 1970 2130.5 1975 2100.4 strength, outliers). 1975 2041.4 c) Write the equation of the regression line for predicting race time from year. 1977 1995.1 1979 1972.5 d) Give the meaning of the slope of your line in terms of race time and year. What are the units of the slope in this problem? 1981 1950.8 1981 1937.2 e) What percent of the observed variation in 1982 1895.3 the race times can be explained by your 1983 1895.0 model? 1983 1887.6 f) Find the residual for the first data point or 1984 1873.8 the list (the 2286.4 seconds from 1967). 1985 1859.4 g) What does this linear model predict for th race time in the year 2075? Do you think 1986 1813.7 this is reasonable?…

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