do fast plz i will 5 upvotes 3.Growth of the Human BrainAgePercentage of theAdult Brain130%250%4678%88%892%1095%1199%relationa) Plot the data in a scatterplot.YA10989b) Using your calculator,find the line of best fit(regression line) and thecorrelation.986-3T3افيا321-2-1-1-2-6-7231335600234568 9 10Xc) Draw the line on thegraph.

Step 1: given data Step 2: Scatter plot is Step 3: Regression line and regression: Step 4: graph…

Answered: 3. Growth of the Human Brain Age…

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015

1st Edition

ISBN:9781680331141

Author:HOUGHTON MIFFLIN HARCOURT

Publisher:HOUGHTON MIFFLIN HARCOURT

Chapter11: Data Analysis And Displays

Section11.3: Shapes Of Distributions

Problem 6Q

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If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
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?
Please help me with question d, e, f, g, h, and I. Thank you.
Which criterion is used for deciding which regression line fits best?
Differentiate between nominal data and ordinal data. Give at least two examples of nominal and ordinal data.
Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R² = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year State the trend line (regression line). y= 3.0161 x -5819.5 year number of vehicle registrations R^2 = 0.9695 not enough information to determine Registrations (in millions)
Let the Explanatory Variable represent the age of a sample of seven randomly selected men. Let the Response Variable represent the corresponding cholesterol measurements of these men. Explanatory Variable: 39, 52, 47, 43, 63, 58, 69 Response Variable: 189, 238, 220, 215, 244, 236, 248 (a) What is the equation of the regression line for this sample data? The y-intercept of your equation must be to three decimal places and the slope of your equation must be to four decimal places. A. y = 2.1664x + 142.336 B. y = 1.8653x + 105.698 C. y = 1.7283x + 135.543 (b) Using the equation of your regression line from (a) above what is the predicted cholesterol measurement when a man is 60 years old? Your answer must be to four places. A. 239.2410 B. 272.3200 C. 217.6160
Let the Explanatory Variable represent the age of a sample of seven randomly selected men. Let the Response Variable represent the corresponding cholesterol measurements of these men. Explanatory Variable: Response Variable: 39, 189, 52, 238, 47, 43, 63, 244, 58, 236, 248 69 220, 215, (a) What is the equation of the regression line for this sample data? The y-intercept of your equation must be to three decimal places and the slope of your equation must be to four decimal places. O A. y = 1.7283x + 135.543 В. y = 1.8653x + 105.698 OC. y= 2.1664x + 142.336 (b) Using the equation of your regression line from (a) above what is the predicted cholesterol measurement when a man is 60 years old? Your answer must be to four places. O A. 217.6160 B. 272.3200 О с. 239.2410
Two lines are proposed to describe the relationship between x and y for a particular data set. Shown below are the lines and the sum of squared error for each line. Line1: yˆ = 5+ 4x, Sumofsquarederror= 48.6 Line2: yˆ = 6 + 3.5x, Sumofsquarederror= 40.8 One of these two lines is the regression line. Which line is the regression line?
The equation that represents the average least squared error and the regression line on the scatterplot is called a: regression equation multiple regression line partial correlation equation slope and intercept line
Predicting Percent Body FatThis problem uses the dataset BodyFat, which gives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (in pounds), Height (in inches), and circumference (in cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist.1Using Neck Circumference to Predict Body FatThe regression line for predicting body fat percent using neck circumference is BodyFat^=-47.9+1.75(Neck). Click here for the dataset associated with this question. (a) What body fat percent does the line predict for a person with a neck circumference of 35 cm?Round your answer to two decimal places.BodyFat^= %What body fat percent does the line predict for a person with a neck circumference of 40 cm?Round your answer to one decimal place.BodyFat^= % (b) One of the men in the study had a neck circumference of 38.7 cm and a body fat percent of 11.3. Find the residual for this man.Round your answer to three decimal places.residual= %…
Whta kind of plot is useful for deciding whether it is reasonable to find a regression plane for a set of data points involving several predictor variables?

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