KAn institution reports many demographic statistics about countries of the world. Data were collected about the Fertility rate (births per woman)and the female Life Expectancy at birth (in years) for 200 countries of the world. The regression output and a scatterplot of the data are shownbelow. Complete parts a through d below.Response variable is: Life expectancy219 total cases of which 19 are missingR squared 71.9%$= 4.303VariableInterceptFertilityCoefficient83.3753-4.54984OA. Yes, an outler occurs at approximately x(Round to one decimal place as needed.)ICCOLife ExpectancyOB. Yes, an outlier occurs at approximately x=(Round to one decimal place as needed.)OC. No, there is no outlier.c) Interpret the value of R². Choose the correct answer below.90-80-70-60-50+40-2FersityThis outier has an unusually high life expectancy given its fertility rate.b) is there an outlier? If so, identify it. Which data value is unusual? Select the correct choice below and, if necessary, fill in the answer box tocomplete your choice.0This outlier has an unusually low life expectancy given its fertility rate.QQG

R-squared value is 71.9%Standard deviation s=4.303.Intercept is 83.3753.Slope is -4.54984.

Answered: An institution reports many demographic…

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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Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $110 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 42 24 119 69 77 48 121 62 5 63 129 21 12 154 4 Gross left parenthesis $ right parenthesis in Millions 117 16 112 66 111 111 104 90 62 104 219 27 20 288 42 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.) The linear coefficient of correlation r = ___ (Round to three decimal places as needed.) The critical value of r = ____ The best predicted gross for a move with a $110 million budget is _____.
The table below displays the population of Hamilton County, Ohio for several different years. Data are from the U.S. Census Bureau. State which variable is the independent variable and which is the dependent variable. Independent Variable: Dependent Variable:
Statistical technique used to determine the degree to which two variables are related is known as a. Regression b. Correlation c. None of these d. Dispersion
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. X Y 11.4 8.4 6.6 13.7 11 9.3 X = thousands of automatic weapons y = murders per 100,000 residents 3.7 7.5 This data can be modeled by the equation y = Answer = 2.4 2.6 2.4 0.4 6.3 5.9 6.2 4.1 to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. Answer = 0.84x +4.01. Use this equation A) How many murders per 100,000 residents can be expected in a state with 6.2 thousand automatic weapons? Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 6.9 thousand automatic weapons? Round to 3 decimal places.
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Instructions: Use the technology of your choice (calculator, Excel, GeoGebra, Google Sheets) to find the regression line, the correlation coefficient of the following data sets, and interpolate or extrapolate the requested data. (Round all numbers to the nearest hundredth, when necessary.) Data Set: {(−3,4),(−2,3),(−1,3),(0,7),(1,5),(2,6),(3,1)}{(−3,4),(−2,3),(−1,3),(0,7),(1,5),(2,6),(3,1)} 1. The regression line is: y=_______ −________x 2. Based on the regression line, we would expect the value of response variable to be _______ when the explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) _________ of _________ in the response variable. 4. If x=−3.5x=−3.5, the yˆ=y^= Answer. This is an example of _______. 5. The correlation coefficient is r=r= Answer. (Round to the nearest hundredth.)
Select the most appropriate response. If the correlation between a person’s age and annual income is 0.60, then the coefficient of determination tells us that: 36% of the variation in a person’s annual income can be explained by the predictor variable age. 36% of a person’s annual income can be explained by their age 60% of the variation in a person’s annual income can be explained by the predictor variable age 60% of a person’s annual income can be explained by their age
Please answer the question on the photo.
Instructions: Use the technology of your choice (calculator, Excel, GeoGebra, Google Sheets) to find the regression line, the correlation coefficient of the following data sets, and interpolate or extrapolate the requested data. (Round all numbers to the nearest hundredth, when necessary.) Data Set: {(0,7),(1,5),(1.5,3),(2,5),(2.3,3.2),(3,2),(3.5,4)}{(0,7),(1,5),(1.5,3),(2,5),(2.3,3.2),(3,2),(3.5,4)} The regression line is: y=y= Answer −− Answer xx Based on the regression line, we would expect the value of response variable to be Answer when the explanatory variable is 0. (NOTE: This is the yy-intercept.) For each increase of 1 in of the explanatory variable, we can expect a(n) Answerdecreaseincrease of Answer in the response variable. (NOTE: This is the slope.) If x=2.5x=2.5, the yˆ=y^= Answer. This is an example of Answerextrapolationinterpolation. The correlation coefficient is r=r= Answer.
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $135 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 45 24 115 74 72 48 117 67 4 60 124 24 6 152 8 Gross left parenthesis $ right parenthesis in Millions 115 10 95 69 127 112 93 101 50 102 223 26 18 282 56 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.)
Tourism is extremely important to the economy of Florida. Hotel occupancy is an often-reported measure of visitor volume and visitor activity (Orlando Sentinel). Hotel occupancy data for February in two consecutive years are as follows. Occupied Rooms Total Rooms Ho: P₁ P₂ #0 Ha: P1 - P2 = 0 Current Year Previous Year Ho: P1 - P2 = 0 Ha: P₁ P₂ #0 Ho: P₁ Ha: P₁ (a) Formulate the hypothesis test that can be used to determine if there has been an increase in the proportion of rooms occupied over the one-year period. (Let p₁ rooms occupied for current year and = P2 population proportion of rooms occupied for previous year.) - Ho: P₁ Ha: P₁ P₂ 0 1,750 1,440 1,800 = population proportion of

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