A regression analysis between sales ( Y in $1,000 ) and advertising (X in $1,000) resulted in the following equation    = 14,200 + 2.6 X   The above equation implies that … … an increase of $ 14,200 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 2,600 in advertising is associated with an increase of $ 1,000 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 2,600 in sales

The following table compares the length of a rhinoceros horn (in inc Use linear regression to find the equation for the line that best fits decimal places. Write your final answer in a form of an equation y = 37 199 203 34 49 46 245 226 40 43 52 55 259 X. 187 230 268

Which is correct?

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 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)

The table lists the cost in millions of dollars for a 30-second commercial for selected years. Year 1994 1998 2004 2008 2011 Cost 33.7 34.2 35.0 35.5 35.9 a. Find a linear function f that models the data. b. Estimate the cost in 2010 and compare the estimate to the actual value of $36.6 million. Did your estimate involve interpolation or extrapolation? a. Use linear regression to determine the equation of the line that best fits the data. The linear function is f(x) = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to three decimal places as needed.)

What is the interpretation of the intercept regression coefficient in a regression model? A. The change in X for a unit increase of Y B. The change in Y for a unit increase of X  C. The estimated value of the dependent variable when X takes the value 1 D. The estimated value of the dependent variable when X takes the value 0

Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ is the predicted final exam score. ?̂ =1.48?+75.64 The scatter plot displays her results. What is the predicted ?̂ value when a student spends 13 hours studying? Round your answer to one decimal place. Select the correct interpretation. The above predicted value of ?̂  is the predicted final math test score if a student studies 13 hours during the year. the predicted score of 13 out of 15 students. what any student will score on the final exam if they study at least 13 hours. the math final test score that 13 students beat.

5. The table below shows varying prices of music sold on a streaming service. Determine the linear regression to estimate the weekly sales of albums sold, use your regression to estimate the weekly sales if the price is $9 per album, and state the correlation coefficient, r, and interpret its meaning in the context of this problem. Price ($) Weekly sales (in thousands) $8 440 $8.50 380 $10 $11.50 250 180

A hotel is monitoring how the number of increases in price affects the weekly profit. The table models the weekly profit, y, after a given number of price increases, x. Which type of models would best fit the data?

Regression analysis was applied between sales (in $1000s) and advertising (in $100s), and the following regression function was obtained. ỹ = 500 + 4x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is $900 $900,000 $40,500 $505,000