1: The depth at which dolphins dive,y, in feet, as related to the duration of the dive,t, in seconds, is represented by the linear model. If the dive duration is 3 seconds, what is the predicted depth of the dive?

0.48 feet

17.59 feet

17.59 feet

0.48 feet

Question 2

Melania is tracking her running training program. The table gives her 5K run time at the end of each month.

Month	Time (in minutes)
1	46
2	42
3	40
4	41
5	38
6	36

What is the equation for the line of best fit, wherexrepresents the month andy-hat represents the predicted time?

Question 3

The weight,y, in pounds, of kittens was tracked for the first 8 weeks after birth, wheretrepresents the number of weeks after birth. The linear model representing this relationship is. David wanted to predict the weight of a kitten at 10 weeks. What is this an example of, and is this method abestpractice for prediction? Explain your reasoning.

This is an example of extrapolation. Extrapolation is a best practice for prediction, as the prediction is accurate even though 10 weeks is outside the given interval of 8 weeks.

This is an example of extrapolation. Extrapolation is not a best practice for prediction, as the prediction is not accurate because 10 weeks is outside the given interval of 8 weeks.

This is an example of linear modeling. Linear modeling is a best practice for prediction, as the prediction is accurate even though 10 weeks is outside the given interval of 8 weeks.

This is an example of linear modeling. Linear modeling is not a best practice for prediction, as the prediction is not accurate because 10 weeks is outside the given interval of 8 weeks.

Question 4

Data were collected on the distance a frisbee will travel when thrown at a certain speed. The speed,s, is measured in miles per hour, and distance,y, is measured in yards. The regression line is given by. What are the slope and y-intercept of the regression line and their interpretation in the context of the problem?

The slope, 3.25, indicates that the distance decreases by an average of 3.25 yards for every one mile per hour of speed. The y-intercept, 46.89, is the distance estimated by this model if the speed is one mile per hour.

The slope, 46.89, indicates that the distance decreases by an average of 46.89 yards for every one mile per hour of speed. The y-intercept, 3.25, is the distance estimated by this model if the speed is one mile per hour.

The slope, 3.25, indicates that the distance increases by an average of 3.25 yards for every one mile per hour of speed. The y-intercept, 46.89, is the distance estimated by this model if the speed is zero miles per hour.

The slope, 46.89, indicates that the distance increases by an average of 46.89 yards for every one mile per hour of speed. The y-intercept, 3.25, is the distance estimated by this model if the speed is zero miles per hour.

Question 5

The IQ scores and English test scores of fifth grade students are given by the regression line, whereis the predicted English score and s is the IQ score. An actual English test score for a student is 65.7 with an IQ of 96. Find and interpret the residual.

2.68; The regression line underpredicts the student's English test score.

2.68; The regression line overpredicts the student's English test score.

2.68; The regression line overpredicts the student's English test score.

2.68; The regression line underpredicts the student's English test score.

Question 6

The data set for a random sample of 10 soccer player's heights compared to their shoe sizes is summarized in the table.

Shoe Size (U.S.)	Height (inches)
7.5	63
8	70.5
12	72
8.5	71
9	69.5
10.5	70
11	75
12.5	64
13	72
10.5	68

Part A:What is the equation of the least-squares regression line? Part B:If a soccer player wears a size 10 and is 68 inches tall, what is their residual? Show all mathematical work. Part C:Interpret the meaning of the residual from part B. explain

*ITS DUE TONIGHT!!!. (please show work for all questions, so i can review, practice, and understand)