Student Year in College Course Work Hours per Class Freshman (1) 2 Sophomore (2) 3 Junior (3) 4 4 Senior (4) A scatterplot of the sample data follows [blue points (circle symbols)]. The line Y = 8 - X is also HOURS 10 O Sum of Distances 8 0 (x-bar, y-bar)) х 5 YEAR Clear All 2. 2. The difference between Y and Ỹ for a particular sample point (observation) is called a residual. Suppose you use the least squares method to find the least squares regression line for the four sample points on the graph. On the basis of your work so far, even before you fit the line, you know that the sum of the residuals is . In addition, being as specific as you can be, you know that the sum of the squared residuals is The slope of the least squares regression line is b = . The intercept of the least squares regression line is a = On the following scatterplot of the blue sample points (circle symbols), use the orange line (square symbols) to plot the least squares regression line. Place the first orange square at the left edge of the graph (the intercept) and the second orange square at the value of Ý at the right edge of the graph. HOURS 10 Regression Line 3 1 3 4. YEAR Clear All

Consider the set of points (0,9),(1,5),(6,3) and (9,2). In this set of points, the age of a dolphin is the first part of each ordered pair and the second part is the number of tricks that the dolphin learned in a month. So, the 6 year-old dolphin learned 3 tricks in the month. Write the least squares regression line for this data. Use the line to estimate how many tricks a 4 year-old dolphin could learn. Then find r and r2. Explain what r2 means.

An engineer wants to determine how the weight of a​ gas-powered car,​ x, affects gas​ mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts​ (a) through​ (d) below.   ​(a) Find the​ least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.   y=nothingx+​(nothing​) ​(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. ​(Use the answer from part a to find this​ answer.)   A. A weightless car will get nothing miles per​ gallon, on average. It is not appropriate to interpret the slope.   B. For every pound added to the weight of the​ car, gas mileage in the city will decrease by nothing ​mile(s) per​ gallon, on…

Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y=82.25 -0.48x. ^ Birthrate, x (number of births per 1000 people) 35.5 44.9 29.7 19.9 13.7 27.0 51.9 15.0 50.9 49.7 39.6 24.4 Send data to calculator Send data to Excel Female life expectancy, y (in years) 67.9 57.9 61.7 71.4 72.5 73.5 55.4 76.5 58.2 60.6 64.4 74.4 Based on the sample data and the regression line, complete the following. Female life expectancy (in years) 85 80+ 75+ 70- 65+ 60- 55+ 50 x X x ++ 10 15 20 25 (b) According to the regression equation, for an increase of one (birth per 1000 people) in birthrate, there is a corresponding decrease…

Weight (pounds), x Miles per Gallon, y 3769 18 3937 15 2662 24 3612 18 3347 20 2917 24 3640 17 2668 24 3381 18 3880 17 3286 19

This is only one question

Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year     Hot Dogs 2015   62 2014   61 2013   69 2012   68 2011   62 2010   54 2009   68 2008   59 2007   66 2006   54 2005   49 2004   54 2003   45 2002     50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question.   (a) Is the trend in the data mostly positive or negative?     Positive   Negative   (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement  20072008 Is the residual positive or…

Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y = 82.17 -0.47x. Birthrate, x (number of births per 1000 people) 14.3 27.4 51.1 46.8 24.9 29.9 18.2 41.6 49.4 14.1 33.9 49.3 Send data to calculator Female life expectancy, y (in years) 75.6 70.5 58.2 59.0 73.3 62.7 73.6 65.2 62.4 74.3 67.0 53.9 Send data to Excel Female life expectancy (In years) Based on the sample data and the regression line, answer the following. 85+ 80+ 75+ 70+ 65 60 55+ 50 (a) From the regression equation, what is the predicted female life expectancy (in years) when the birthrate is 29.9 births per 1000 people? Round your answer to…

The defending attorney Mr. Justin Case was interested in how a lengthy trial could affect howlong a jury would deliberate on a case (and see if he should just cut to the chase). He observed asample of courtroom trials and noticed the following:Days inTrial (X) 5 2 6 4 5 6 2 4 2 1  HoursDeliberation (Y) 4 4 1 3 1 3 9 2 3 7 1) What is the slope of the regression line?

For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002. The variable x denotes the player payroll (in millions of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, x (in Mean attendance, y (in $1,000,000s) thousands) Anaheim 62.8 28.52 Baltimore 56.5 33.09 40- Boston 110.2 32.72 35 Chicago White Sox 54.5 20.74 30- Cleveland 74.9 32.35 25- Detroit 54.4 18.52 Kansas City 49.4 16.30 15- Minnesota 41.3 23.70 10+ New York Yankees 133.4 42.84 Oakland 41.9 26.79 20 40 60 80 100 120 140 Seattle 86.1 43.70 Player payroll, Тarmpa Bay 34.7 13.21 X (in $1,000,000s) Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator Send data to Excel Based on the sample data and…