QUESTION 4In a hypothesis test for linear regression, we will most often test if theline of best fity-interceptrelationship between variablesO slopeis significant.

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College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 8PT: Does Table 1 represent a linear function? If so, finda linear equation that models the data.

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Does Table 1 represent a linear function? If so, finda linear equation that models the data.
Which of the variables is the indepenent variable and dependent variable for the following question. fit a simple linear regression model to predict latitudes using average monthly range lat= latitudes range= the average monthly range between mean montly maximum and minimum temperatures for a selected set of US cities.
If a new independent variable is added to a regression equation, the adjusted R2 increases only if the absolute value of the t-statistic of the new variable is greater than one. Group of answer choices True False.
Which is an assumption of linear regression analysis? The mean of the residuals should be
A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking related to the risk of strokes. The data file “Stroke.xslx” includes a portion of the data from the study. The variable “Risk of Stroke” is measured as the percentage of risk (proportion times 100) that a person will have a stroke over the next 10-year period. Regression Analysis As Image: 1) Based on the simple regression analysis output, write the estimated regression equation. 2) What is the correlation coefficient between Risk of Stroke and Age? How do you find i
If 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.
Which pair of h0/h1 is used in the two sided test for the slope of a simple linear regression?
In a simple linear regression prediction equation, the slope is defined as which of the following? The slope is the value of X when Y = 0. For a one-unit change in Y (the criterion), there will be a slope-unit change in X (the predictor) For a one-unit change in X (the predictor), there will be a slope-unit change in Y (the criterion) The slope is the value of Y when X = 0.
The following result perspective in RapidMiner shows a multiple linear regression model. Based on the diagram, the model for our dependent variable Y is Predicted Y= (Insulation *0.420)+(Temperature *0.071)+(Avg_Age*0.065)+(Home_Size *0.311)+7.589 Attribute Insulation Temperature Avg Age Home Size (Intercept) O True O False Coefficient 3.323 -0.869 1.968 3.173 134.511 Std. Error 0.420 0.071 0.065 0.311 7.589 Std. Coefficient 0.164 -0.262 0.527 0.131 ? Tolerance 0.431 0.405 0.491 0.914 ? t-Stat 7.906 -12.222 30.217 10.210 17.725
Give examples of where the use of regression analysis can be benificially be made.

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In a hypothesis test for linear regression, we will most often test if the O line of best fit y-intercept relationship between variables slope is significant.