QUESTION 20 1 POINT A medical experiment on tumor growth gives the following data table. Previous X 45 72 88 92 115 y 33 57 98 99 100 ٹی 21/2 The least squares regression line was found. Using technology, it was determined that the total sum of squares (SST) was 3789.2 and the sum of squares of regression (SSR) was 3192.4. Calculate R², rounded to three decimal places.
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- If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?Researchers found a positive assodation between the students' performance in STAT 1000 and their first-year cumulative college GPA. Furthermore, STAT 1000 course GPA explained 62% of the variation in students'first-year cumulative college GPA. The summarized data is given below: Mean STAT 1000 GPA = 25 Std. dev. - 0.21 Mean cumulative College GPA = 325 Std. dev, = 03 The slope and intercept of the least squares regression line for predicting first-year college GPA from STAT 1000 scores are, respectively. Oa Slope 055 Intercept 1.88 Ob Slope = 1.12 Intercept 1.88 Oc Slope = 1.12 Intercept 044 Od. Slope 044 Intercept 055 Oe Slope- 1.88 Intercept 055A group of 13 healthy children and adolescents participated in a phycological study designed to analyze the relationship between age and average total sleep time (ATST). To obtain a measure for ATST (in minutes), recordings were taken on each subject on three consecutive nights and then averaged. Results are provided to you in Sleep&Age.xlsx Download Sleep&Age.xlsx file. (2 points) Determine the least-squares regression line for predicting average total sleep time using age. (2 points) Make a scatter plot of the data with ATST on the y-axis (vertical axis) and Age on the x-axis (horizontal axis) with least squares regression line overlaid on the top (i.e.: obtain the fitted line plot). Make sure to attach the plot below. (7 points) Check the assumptions for the simple linear regression. Attach any plots you used check the assumptions and comment on them. (7 points) We want to see if the average sleep time decreases as the children grow older. Write the appropriate null and…
- A researcher wishes To determine the relationship between the number of Cows(in thousands) in counties in southwestern Pennsylvania and the milk production ( in millions of pounds.) After computing the least squares regression line, it is determined that r^2=0.9972. Which of the following is the correct interpretation of this value? Answer Choices: A.) none of the other answers is a correct interpretation B.) About 99.72% of the changes in the number of cows are explained by changes in milk production C.) About 99.72% of the change in milk production are explained by changes in the number of cows.Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ?X is the age of the crab in months and ?ˆY^ is the predicted value of ?Y, the size of the male crab in cm. ?ˆ=9.1367+0.4817��Y^=9.1367+0.4817X What is the value of ?ˆY^ when a male crab is 22.1725 months old? Provide your answer with precision to two decimal places.Hello, I am working on an assignment in research design. How do I calculate cronbach's alpha for a multiple regression analyis of prayer on a set of 5 different vital signs? (heart rate, blood pressure, temp, O2, and resp)
- For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the National League teams in the year 2002 . The variable x denotes the player payroll (in millions of dollars) for the year 2002 , and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in Figure 1 scatter plot, as is the least-squares regression line. The equation for this line is =y+5.910.34x . Answer the following: 1. Fill in the blank: For these data, mean attendance values that are less than the mean of the mean attendance values tend to be paired with player payroll values that are _____ the mean of the player payroll values. Choose onegreater thanless than 2. Fill in the blank: According to the regression equation, for an increase of one million dollars in player payroll, there is a corresponding _____ of 0.34 thousand fans in mean attendance. Choose…The least-squares regression line for predicting y = clutch size from x = snout-vent length is = -144 + 6.123 x. The paper also reported r2 = 0.7499 and SSTo = 46419. Find the value of se (the sample size was n = 14). (Give the answer to two decimal places.)Please analyze these tables one by one . Explain as table 1 and table 2.
- A recent study showed that the hours a person exercised in a week affected the individual'sresting heart rate. It was computed that r = -.68 and the least squares regression line was?̂ = 83-1.4x, where x is the hours exercised and y is the resting heart rate. d. What percentage of variability in resting heart rate can be explained by variability inhours exercised?You want to look at an ANOVA table of a regression in which a dependent variable is predicted using an intercept and one slope coefficient. Unfortunately, as you want to look at the table, you knock over your coffee mug which smudges out some of the numbers. Here is what you still can read: • n=7 • F-ratio = 15 • Residual sum of squares (RSS) = 16 • t-score of the slope coefficient = 3.873 How big is the explained sum of squares (ESS)? a 44 b 52 c 48 d 40 How big is the total sum of squares (TSS)? a 64 b 52 c 60 d 56 How big is the explained R-squared? a 0.7 b 0.75 c 0.8 d Cannot be determined What's the p-value for the F-ratio? a 0.012 b 0.024 c 0.036 d…Interpret the least squares regression line of this data set. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The correct least squares regression line for the data set is: y = 8.116x + 273.273 Use it to complete the following sentence: The least squares regression line predicts an additional annual rainfall if the average temperature of coastal waters increases by one degree millimetres of Celsius.