Number of Average Employees Xm FXm Xm-X f(Xm-X)2
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![Number of
Average
Employees
Xm
FXm
Xm-X
f(Xm-X)2
<cf
Production
A
61-65
66-70
71-75
11
76-80
17
81-85
12
86-90
91-95
4
60
Mean
median
variance
sd
skewness
CO](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F57450ae3-27ec-49fb-a71a-ea2b2f3654cc%2F63b2d1e8-85ad-4369-aeae-166de880c4c5%2F348yhd_processed.jpeg&w=3840&q=75)
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- The regression equation is Health Index= y + a Age + ß Blood sugar + 8 Blood Pressu SE 20986 Coef 2912 339.28 71.95 Age Blood sugar 209.2 179.3 Blood pressure 207.2 225.4 S = 962.233 R-Sq = 86.6% R-Sq (adj) = 76.5% Coef Constant Analysis of Variance Source DF Regression 3 Residual Error 4 Total 7 SS 23863180 3703570 27566750 MS T 7.21 4.72 * 0.92 7954393 925892 F *** P 0.002 0.009 0.308 до 0.032 a) What is dependent and independent variables? b) Fully write out the regression equation. c) Fill in the missing values **, ***', and *****. d) Hence test whether & is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis.Calculate an estimate of the error standard deviation in the simple regression modelA doctor notes the variables listed in the following table from every patient before admitting in his hospital. Which of the following variables are qualitative and which are quantitative? Which qualitative variables are nominal or ordinal? Which quantitative variables are discrete or continuous? ( 1 ) Gender (Male or Female) ( 2 ) Weight (lbs) ( 3 ) Phone Number ( 4 ) Height (cm) ( 5 ) Marital Status (Single, Married, Divorce, Widow) ( 6 ) Systolic Blood Pressure (mm of pressure) ( 7 ) Temperature (degree F) ( 8 ) Level of Calcium (microgram/milimeter) ( 9 ) Family of Income ( Amount) ( 10 ) Wihte Blood Cells
- Select all the charts that violate the conditions for linear regression. These are residual plots so the red line represents the average residual, zero. 미 Od (a) (d) 매 Get help: Video (b) (e) (c) (1)23:01 Done A S Male (X2) = binary variable (1 if male, 0 if female) Age (X3) = age in years North (X4) = binary variable (1 if Region = North, 0 otherwise) South (X5) = binary variable (1 if Region = South, 0 otherwise) East (X6) = binary variable (1 if Region = East, 0 otherwise) Using the regression results in column (1): The calculated test statistic is_ The table below contains three estimated regressions, which were computed in 2007 using data on employees. The data set used for the regressions consisted of information on over 10,000 full-time, full-year workers. Employees were surveyed on their earnings and whether they had graduated high school or not. The data set also contains information on the region of the country where the person lived (North / East / South / West), and the individual's gender and age. (plz write in 2 decimal places) is the null hypothesis rejected at the 5% level of significance?_ DO For the purposes of this quiz: AHE = average hourly earnings Graduated…Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative?
- Multiple regression analysis was used to study how an individual's income (Y in thousands of dollars) is influenced by age (X1 in years), level of education (X2 ranging from 1 to 5), and the person's gender (X3 where 1 =female and 0=male). The following is a partial result of a computer program that was used on a sample of 30 individuals. Coefficient Standard Error X1 0.63 0.094 X2 0.94 0.190 X3 0.52 0.120 Analysis of Variance Source of Degrees Sum of Mean Variation of Freedom Squares Square F Regression 90 Error 100 Use the above results and write the…WEEK TWO Day_1 (1).pdf Microsoft Word - WEEK TWO 38e53478cfbbc97a28d/MyFiles/Downloads/WEEK_TWO_Day 2%20(1).pdf 1/ 2 100% 6. What is the slope of any line parallel to the line 2r-3y 7? F.-3 2 G. H. J. 2 K. 3 (Test 2 #8)3. Correlation and linear regression
- A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x₁ = distance traveled (miles) and x₂ = the number of deliveries made. Suppose that the model equation is Y = -0.800+ 0.060x₁ +0.900x₂ + e (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? hr (b) How would you interpret ₁ = 0.060, the coefficient of the predictor x₁? O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a one-mile (i.e.…The average August temperatures (y) and geographic latitudes (x) of 13 cities in the United States were studied. The regression equation for these data isTemperature = 127 -1.68*(latitude)What is the slope of the line? Estimate the mean August temperature for a city with latitude of 11.Use 2 decimal placesSan Francisco has a latitude of 40. What would you predict for the mean August temperature of San Francisco?Use 2 decimal placesGiven that the mean August temperature in San Francisco is actually 70 calculate the residual (prediction error) for San Francisco.It should be observed minus predicted. If you do it wrong your answer have the positive and negative switchedUse 2 decimal placesThe latitude at the equator is 0. Estimate the average August temperature at the equator.Use 1 decimal place24. A bivariate regression was conducted to determine the time to failure (seconds) based on the number of push-ups conducted, what term describes when the line of best fit crosses the vertical axis? Outlier Y-intercept Intercept
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