a) Compute the correlation coefficient relating introversion and shyness scores. b) Find the regression equation which predicts introversion from shyness. c) What introversion score would you predict from a shyness score of 7?
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- The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 47 48 56 60 67 Bone Density 359 350 334 314 313 Find the estimated slope. Round your answer to three decimal places.A team from UNHABITAT took a random sample of 230 households in a city to better understand how the size of a house (measured in metres) is related to the number of people living in that house. They performed a regression analysis on the data and found that regression model had an R² = 18.3%. What is the correlation between the size of a house and the number of people living in that house? 0.667 0.183 0.033 0.904 0.428The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 37 40 52 60 67 Bone Density 352 351 336 329 319. Find the estimated slope. Round your answer to three decimal places
- The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 0 0.5 2 3 4.5 5 6 Overall Grades 99 98 96 92 89 88 80 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer to three decimal places.a tab = The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, bo + bx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Answer How to enter your answer (opens in new window) esc Step 3 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable . Google Play Store alt 1…Does more education lower a person’s level of prejudice? The number of years of education and the score on a prejudice test for ten people is given in the following table. Higher scores on the test indicate more prejudice. Years of Education: 12, 15, 14, 13, 18, 10, 16, 12, 10, 4Score of Prejudice Test: 1, 6, 2, 3, 2, 4, 1, 5, 5, 10 The regression equation is calculated to be y' = 10.5 - 0.532x. After conducting a hypothesis test, your decision is to reject the null hypothesis. Predict the value of y' when x=11. 10.5 4.645 1.945 0.749
- a) what is the regression equation? b) what is the predicted weight of the bear? c) is the result close to the actual weight of 528 pounds?Why was the variable “# of customer service representatives” dropped from the model? Write the regression equation. Sales of men’s clothing (predicted) = Are the regression coefficients significantly different from 0? If one mails 10,000 catalogs and has 15 phone lines open, what would the predicted sales of men’s clothing be? How would you interpret the regression coefficient for number of catalogs mailed? What is the final R2 of the model? How would you interpret this? Which of the two independent variables is the most important predictor of the dependent variable? Why?You do a survey where you ask people both their age and their income. You want to see if there is a relationship between these two variables, and you want to create an equation you can use to predict someone’s age from his/her income. What kind of hypothesis test or analysis should you do?a. One-Factor, Independent-Measures ANOVAb. Two-Factor ANOVAc. Correlation/Regressiond. Chi-Square Goodness of Fit
- The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density48 35151 32056 31860 31169 310 Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 0.5 1 2.5 3 4 5 5.5 Overall Grades 98 95 90 79 75 69 66 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: Determine if the statement "Not all points predicted by the linear model fall on the…The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 35 43 53 54 55 Bone Density 350 340 339 321 310 Table Step 6 of 6 : Find the value of the coefficient of determination. Round your answer