In the following problems, find the equation of the least squared regression line and the correlation coefficient. Then perform a hypothesis test to determine if there is a significant relationship between the two variables. Use the p-value method and show all 5 steps of the hypothesis test. Test at a= 0.05 2. A random sample of scoring leaders in the NHL showed the following numbers of assists and total points. Assists, x 26 29 32 34 36 37 40 Total Points, y 48 68 66 69 76 67 84

In the following problems, find the equation of the least squared regression line and the correlation coefficient. Then perform a hypothesis test to determine if there is a significant relationship between the two variables. Use the p-value method and show all 5 steps of the hypothesis test. Test at a= 0.05 2. A random sample of scoring leaders in the NHL showed the following numbers of assists and total points. Assists, x 26 29 32 34 36 37 40 Total Points, y 48 68 66 69 76 67 84

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states, where T is thousands of automatic weapons and y is murders per 100,000 residents. 11.4 8.1 6.7 3.3 2.3 2.6 2.1 0.7 13.6 10.6 9.6 6.9 5.9 6.4 6. 4.9 Use your calculator to determine the equation of the regression line and write it in the y = ar +b form. Round to 2 decimal places. y = .78x +4.39 According to this model, how many murders per 100,000 residents can be expected in a state with 2.1 thousand automatic weapons? Round to 3 decimal places. 5.9 According to this model, how many murders per 100,000 residents can be expected in a state with 7 thousand automatic weapons? Round to 3 decimal places. 9.82
Provide a detailed interpretation analysis of the regression results below. Pay attention to the main tested variables, model fit characteristics (R 2 ) and number of respondents in the sample. State what is dependent and what are independent variables. Was the hypotheses rejected or confirmed? a) H1: If a woman has a job she will have less children born b) H2: The younger a woman got married the more children she has c) H3: Education positively affects number of children to have
a. Calculate the sample covariance.X Y-3 -913 95 12b. Calculate the sample correlation.c. Describe in words the information given to us by the sample covariance and by the sample correlation.Explain how the correlation gives us more precise information.d. Explain why the covariance is not a good measure of the strength of the linear relationship between the twovariables.e. Sketch a scatterplot of a bivariate dataset with a correlation of 0.9f. Sketch a scatterplot of a bivariate dataset with a correlation of -0.3.
An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)
a. Estimate the regression line and also write the prediction equation. y = 83.4578-5.8795 x y = 5.8795 + 83.4578 x ŷ ŷ= = -5.8795 + 83.4578 x = 83.4578 + 5.8795 x
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
Suppose you are a dolphin trainer at SeaWorld. You teach the dolphins by rewarding them with fish treats after each successful attempt at a new trick. The following table lists the dolphins, the number of treats per success given to each, and the average number of attempts necessary for each to learn to perform the tricks. Dolphin Number of Treats Number of Attempts Diana 2 Frederick 4 Fatima Marlin Ŷ = bX + a You can use the preceding sample data to obtain the regression line, where Ŷ is the predicted value of Y: b = One formula for the slope of the regression line is as follows: SP = To calculate the slope, first calculate SP and SSx: 1 3 and SSx = ∞587 (Hint: For SP use the computational formula and for SSx use the definitional formula.) The slope of the regression line is Frederick Fatima Marlin The difference between Y and Ŷ for a particular sample point (observation) is called a residual. Calculate the predicted Y (Y) for each of the dolphins, and then calculate the residuals. 4…
The coefficient of determination (r2) is a measure of the: a.) amount of variance in the dependent variable explained by the independent variable. b.) correlation between two variables. c.) variability of the dependent measure. d.) slope of a regression line.
Suppose you are a dolphin trainer at SeaWorld. You teach the dolphins by rewarding them with fish treats after each successful attempt at a new trick. The following table lists the dolphins, the number of treats per success given to each, and the average number of attempts necessary for each to learn to perform the tricks. Dolphin Number of Treats Number of Attempts Diana 4 5 Frederick 2 8 Fatima 1 8 Marlin 3 7 You can use the preceding sample data to obtain the regression line, where Ŷ is the predicted value of Y: ŶŶ = = bX + abX + a One formula for the slope of the regression line is as follows: bb = = SPSSxSPSSx To calculate the slope, first calculate SP and SSxx: SP = __?__ , and SSxx = _?_ . (Hint: For SP use the computational formula and for SSxx use the definitional formula.) The slope of the regression line is , and the Y intercept of the regression line is ___?__ . The difference between Y and…
Please answer A,B, D, F, & G pls and thank you!