NormalNo SpacingHeading 1EditingDictateStylesVoiceSens2. For each of the following datasets, identify any regression outliers and anyinfluential observations. Remember that regression outliers are data points thatappear to deviate from the trend of the data. Influentiaí observations are datapoints whose removal would have a significant effect on the regression model.Influential observations often also have high leverage, meaning they tend toappear far in the horizontal direction from the other data values.a.x (independent)914.25.57.71944y (dependent)-11-134.9-1.6-4-26-30-81C18 SA18 - 1 921 C1740b.x (independent) 12.2y (dependent)16.921.722.525.43055626.7.13.81415.2OFocus

Answered: Image /qna-images/answer/b9786f71-1781-455a-94d3-b6842395d64b.jpg

Answered: 2. For each of the following datasets,…

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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The following data gives the number of employees at the bookstore and the number of minutes students wait in line to buy books at the beginning of the term. The independent variable is the number of employees and the dependent variable is the number of minutes. What is the y intercept? SSxx = 56.857; SS=2095.714; SSxy=-322.571 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square XA356899 0.96 0.93 0.91 y 67 54 47 33 31 25 12
2. Following data is amount of Assessed Value for an office building for a given floor area, number of office space, number of entrances, and the age of the offic building. Use excel to …. Obtain a Scatter plot of Floor Area as the independent and Assessed value as the dependent variable. Note the linear regression Model Predict the assessed value for 6000 sq ft. FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4 2 8 1796 4720 3 2 12 1544 5940 4 2 2 2094 5720 4 2 34 1968 3660 3 2 38 1567 5000 4 2 31 1878 2990 2 1 19 949 2610 2 1 48 910 5650 4 2 42 1774 3570 2 1 4 1187 2930 3 2 15 1113 1280 2 1 31 671 4880 3 2 42 1678 1620 1 2 35 710 1820 2 1 17 678 4530 2 2 5 1585 2570 2 1 13 842 4690 2 2 45 1539 1280 1 1 45 433…
Interpret the intercept and the slope coefficient of the estimated linear trend line equation and comment on the fitness of the model.
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 11 8 11 13 6 13 6 y 7.24 6.87 12.78 6.87 7.75 8.85 6.28 5.61 8.28 6.72 5.52 Create a scatterplot of the data. Choose the correct graph below. VA. OB. OC. OD. 25- Ay 25- 25- 25- 20- 20 20- 20 15 155 155 155 10- 10- 10 10- 5- 5- 5 55 0- 05 10 15 20 25 0- O 5 10 15 20 25 04 05 10 15 20 25 0- 05 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.)
Personal wealth tends to increase with age as older individuals have had more opportunitiesto earn and invest than younger individuals. The following data were obtained from a randomsample of eight individuals and records their total wealth (Y) and their current age (X). See attachment for table with figures State the estimated regression line and interpret the slope coefficient.b. What is the estimated total personal wealth when a person is 50 years old?c. What is the value of the coefficient of determination? Interpret it.d. Test whether there is a significant relationship between wealth and age at the 10%significance level. Perform the test using the following six steps.Step 1. Statement of the hypotheses Step 2. Standardised test statistic Step 3. Level of significance Step 4. Decision Rule
9. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 160 130 330 120 70 190 (a) x = 170 calories (c) x = 150 calories 180 (b) x = 80 calories 420 470 360 250 530 (d) x = 210 calories Find the regression equation. x+( (Round to three decimal places as needed.) y = Choose the correct graph below. OA. О В. OC. OD. 560- 560 560 560- 200 G 0IN T> 200 200 Calories Calories Calories Calories (a) Predict the value of y for x = 170. Choose the correct answer below. O A. 411.632 O B. 543.752 O C. 455.672 O D. not meaningful (b) Predict the value of y for x = 80. Choose the correct answer below. O A. 411.632 О В. 257.492 O C.…
Plot 1 Out-of-State Tuition Plot 1: Out-of-State Tuition vs Student-Faculty Ratio 20000 15000 10000 5000 10 20 Student-Faculty Ratio 30 40 Expenditure Category • Above Average Expenditure • Below Average Expenditure
derwin
Here is data with y as the response variable. a. Make a scatter plot of this data. Which point is an outlier? Enter as an ordered pair, e.g., (x,y). (x, y) b. Find the regression equation for the data set without the outlier. Enter the equation of the form mx + b rounded three decimal places. y wo X 48.4 77.3 88 67.1 108.3 75.9 64.8 -161.3 61.2 67.9 ŷw y 45.7 40.3 27.3 54.5 -63.2 36.3 73.2 96.5 82.2 119.8 = -- c. Find the regression equation for the data set with the outlier. Enter the equation of the form mx + b rounded to three decimal places.
The correct answer is option C but I do not know how to find the number that go inside it.

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