2. For a linear regression model including only an intercept, the OLS estimator of that intercept is equal to the sample mean of the independent variable.
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- Suppose the following data were collected from a sample of 5 car manufacturers relating monthly car sales to the number of dealerships and the quarter of the year. Use statistical software to find the following regression equation: SALESi= b0 + b1DEALERSHIPSi + b2 QUARTER1i+ b3QUARTER2i + b4QUARTER3i+ ei Is there enough evidence to support the claim that on average, car sales are higher in the 4th quarter than in the 2nd quarter at the 0.01 level of significance? If yes, write the regression equation in the spaces provided, rounded to two decimal places. Else, select "There is not enough evidence." Monthly Sales Number of Dealerships 1st Quarter (1 if Jan.-Mar., 0 otherwise) 2nd Quarter (1 if Apr.-Jun., 0 otherwise) 3rd Quarter (1 if Jul.-Sep., 0 otherwise) 4th Quarter (1 if Oct.-Dec., 0 otherwise) 85482 4 1 0 0 0 101319 9 1 0 0 0 121389 12 1 0 0 0 133677 18 1 0 0 0 194588 22 1 0 0 0 82128 4 0 1 0 0 150407 9 0 1 0 0 242714 12 0…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, y = bo + b,x, 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 2 3 4.5 Overall Grades 99 98 96 92 89 88 80 Table Copy Data Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Consequently, the appraiser decided to fit the simple linear regression model, y = b₁x + bowhere y = appraised value of the house (in $thousands) and x = number of rooms. Using data collected for a sample of n=74 houses in East Meadow, the following results were obtained: y = 74.80 + 17.80x Give a practical interpretation of the estimate of the slope of the least squares line. For each additional room in the house, we estimate the appraised value to increase $74,800. For each additional dollar of appraised value, we estimate the number of rooms in the house to increase by 17.80 rooms. For a house with O rooms, we estimate the appraised value to be $74,800. For each additional room in the house, we estimate the…
- Given the equation of a regression line is y= -1.5x-1.8, what is the best predicted value for y given x= -3.0? Assume that the variables x and y have significant correlation.We wants to assess the relationship between overall GPA (4.0 scale) and amount of time spent weekly on school work of 50 college students. Simple linear regression model is used and some results for the model is given: a) Is it plausible that the true intercept for the model is 2.0? Why or why not? (hint: using interval for intercept) b) If 2.0 is the real intercept for the model, does it make contextual sense? Explain why it is or why it is not. c) Using the model, calculate the number of hours needed to achieve a GPA of 4.0. Then explain why this estimate number of hours is biased. (hint: think about Y).Suppose you are examining a multi-variable linear regression model that was designed to predict the weight of a person, measured in kg, using 3 predictor variables. One of the variables used in this analysis is "height", with the coefficient of this variable being equal to 3.96, with a standard error of the coefficient equal to 1.168. There are 300 datapoints in the dataset. Using this information, what would be the test statistic (t-ratio) for the test to see if the variable "height" is significant? Only round final answer. Round to two 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…If a correlation isr= 0.00, then SP = 0 and the regression equation is O Ý =X +0 O Ý =X + X O Ý =0 + X O Ý =Ÿ + 0If a regression line for two variables has a small positive slope, then the: variables are positively associated? variables are negatively associated? association of the variables cannot be determined. variables have no association with each other.
- A researcher has developed a regression model from fourteen pairs of data points. He wants to test to determine if the slope is significantly different from zero. He uses a two-tailed test and a = 0.01. The critical tablet value is 2.718 3.012 2.650 O 3.055 O 2.168The 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 + 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. a Answer How to enter your answer (opens in new window) Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. 9 S e $ A A Hours Unsupervised Overall Grades V 96 5 t 8 b Oll 0 0.5 1 3.5 4 5 5.5 95 92 85 83 81 73 63 h → U İ 8 i k N 9 O alt I * Р ctri Tables Copy Data Keypad Keyboard Shortcuts Previous step answers…A 1 Demand 2 WN 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 7.38 8.51 9.52 7.50 9.33 8.28 8.75 7.87 7.10 8.00 7.89 8.15 9.10 8.86 8.90 8.87 9.26 9.00 8.75 7.95 7.65 7.27 8.00 8.50 8.75 9.21 8.27 7.67 7.93 9.26 B PriceDif -0.05 0.25 0.60 0.00 0.25 0.20 0.15 0.05 -0.15 0.15 0.20 0.10 0.40 0.45 0.35 0.30 0.50 0.50 0.40 -0.05 -0.05 -0.10 0.20 0.10 0.50 0.60 -0.05 0.00 0.05 0.55 C
