2.1. Give one word for the following statements or scenarios:2.1.1. The data collected by the researcher from the Department of Education were the 2020 matricresults for all South African high schools in disadvantaged areas..2.1.2. This analysis can be performed using either the method of moving averages, or by fitting astraight line using the method of least squares from regression analysis.

Given Information: Consider the given two Scenarios

Answered: 2.1. Give one word for the following…

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 data in the table represent the number of licensed drivers in various age groups and the number of fatal accidents within the age group by gender. Complete parts (a) through (c) below. Click the icon to view the data table. ..... (a) Find the least-squares regression line for males treating the number of licensed drivers as the explanatory variable, x, and the number of fatal crashes, y, as the response variable. Repeat this procedure for females. Find the least-squares regression line for males. y =x+O %D/ (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) Find the least-squares regression line for females. y = ý =x+O %3D (Round the x coefficient to three decimal places as needed. Round the constant to the nearest integer as needed.) (b) Interpret the slope of the least-squares regression line for each gender, if appropriate. How might an insurance company use this information? What is the correct interpretation of the…
The management at a company that sells and services exercise equipment would like to determine if there is a relationship between the number of minutes required to complete a routine service call and the number of machines serviced. A random sample of 12 records revealed the information available below concerning the number of machines serviced and the time (in minutes) to complete the routine service call. Complete parts a and b below. E Click the icon to view the data. .... a. Estimate the least squares regression equation. The regression equation is y=() x. (Round to two decimal places as needed.) b. If a gymnasium had nine machiìnes, how many minutes should the company expect a routine service call to require. A routine service call should require about minutes if there are nine machines. (Round to the nearest minute as needed.) - X Cost of Small Projects Data Number of Machines Service Time (minutes) 12 115 65 80 10 9 85 50 60 65 40 7 9. 3 11 95 4 45 5 11 35 105 Print Done
Answer the 2 questions from the page with the question starting with "Give a practical interpretation..."
7. A study was conducted at Virginia Tech to determine if certain static arm-strength measures have an influence on the "dynamic lift" characteristics of an individual. Twenty-five individuals were subjected to strength tests and then were asked to perform a weightlifting test in which weight was dynamically lifted overhead. The data are given here. Estimate the linear regression line. Arm Dynamic Lift, y 71.7 Individual Strength, a 17.3 19.3 19.5 48.3 88.3 19.7 75.0 22.9 23.1 26.4 26.8 27.6 28.1 28.2 28.7 29.0 29.6 91.7 100.0 73.3 65.0 75.0 88.3 68.3 11 12 96.7 13 76.7 14 78.3 15 29.9 29.9 60.0 71.7 16 I 17 18 19 30.3 85.0 31.3 36.0 85.0 88.3 100.0 100.0 100.0 20 21 39.5 40.4 22 44.3 23 44.6 91.7 100.0 24 50.4 25 55.9 71.7
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
Answer the following: 2. Describe the form, direction, and strength of the relationship between these variables. Does there appear to be any outliers? 3. The equation of least-squares regression line is y = 6.871 + 0.061x. This line goes through the points (0, 6.9) and (700, 49.5). Use these points to add the regression line to your scatterplot above. 4. One animal is farthest from the regression line and is an outlier for these two variables. Find the name of this animal and write a sentence describing how its position differs from the overall relationship among the other animals. 5. The elephant has the longest gestation period of these animals. a. Considering only the gestation variable, would you say that the elephant is an outlier? Write a sentence or two explaining why or why not? b. Considering both variables and the relationship between average life span and average gestation period, would you say the elephant is an outlier now? Write a sentence or two explaining why or why…
The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Month Jan Feb Mar Apr Number of Accidents 25 48 70 90 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): y = Using least-squares regression, the forecast for the number of accidents that will occur in the month of May = accidents (enter your response as a whole number).
A study was conducted to investigate the effect of vehicle weight on gas mileage. The following random sample was collected where x is the weight of a vehicle in pounds and y is the miles per gallon. a. Write a sentence interpreting the value of the slope of the regression line. b. If a vehicle weighs 4000 pounds, what does the least-squares line predict for the miles per gallon? (Show your calculations.) Is this interpolation or extrapolation? Explain. c. What does the correlation coefficient tell us about the relationship between weight and gas mileage? d. Give a brief explanation of the meaning of the coefficient of determination in the context of this problem.
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage. v. The une ory tor ine most recent m odel year. Complete parts (a) through (d) accompanying data represent the weights of various domestic cars and their miles per gallon in BEE Click here to view the weight and gas mileage data (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y = 0.00702 * + (43.2) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice.answer trom part a to find this answer O A. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. A weightless car will get miles per gallon, on averag B. For every pound added to the weight of the car, gas…
3. In a study of 1991 model cars, a researcher computed the least-squares regression line of price (in dollars) on horsepower. He obtained the following equation for this line. Price = -6677 + 175 × Horsepower
Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)
#3. What is the least squares regression line for the following set of data? y-hat = 2.18x + 27.74 y-hat = 2.14x + 27.44 y-hat = 1.94x + 26.24 y-hat =1.86x + 26.28

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