Fun Stats

A fisheries biologist studying whitefish in a Canadian Lake collected data on the length (in CM) and eg production for 25 female fish. A scatter plot of her results and computer regression analysis of egg production versus fish length are given below. (Note: number of eggs is given in 1000's so 40 means 40,000 eggs). Which of the following statements can be made on the basis of the computer output?

• 83.5% of the variation in egg production can be accounted for by the LSRL of egg production on fish length

• 69.7% of the variation in egg production can be accounted for by the LSRL of egg production on fish length

• 83.5% of the variation in fish length can be accounted for by the LSRL of egg production on fish length

• 69.7% of the variation in fish length can be accounted for by the LSRL of egg production on fish length

• 68.4% of the variation in fish length can be accounted for by the LSRL of egg production on fish length

You are examining the relationship between x = the height of red oak trees and y = the number of acorns produced in a five year period. You calculate a correlation coefficient and a least-squares regression line of y on x. If you switched the variables (that is, let x = number of acorns and y = height of trees), which of the following would be true?

• both the correlation coefficient and the regression line would be unchanged

• the correlation coefficient would change, but the regression line would not change

• the correlation coefficient would not change, but the regression line would change

• neither the correlation coefficient nor the regression equation would change

• only the y-intercept fo the regression line would change, the slope of the line and the correlation coefficient would not change.

A simple random sample of 25 world-ranked tennis players provides the following statistics: Number of hours of practice per day: x-bar = 7.3, standard deviation of x = 1.2. Yearly winnings: y-bar = $1,820,000, standard deviation of y = $310,000. Correlation r = .23. Based on this data, what is the resulting linear regression equation?

• predicted winnings = 1,390,000 + 59,400(hours)

• predicted winnings = 1,300,000 + 71,300(hours)

• predicted winnings = -63,400 + 258,000(hours)

• predicted winnings = -443,000 + 310,000(hours)

• predicted winnings = -10,000,000 + 1,620,000(hours)

The height (in feet) and volume (in cubic feet) of usable lumber of 32 cherry trees are measured by a researcher. The goal is to determine if volume of usable lumber can be estimated from the height of a tree. In this study, the response variable is......

• height of researcher

• volume of lumber

• height of tree

• the measuring instrument used to measure volume

• impossible to determine

How is the data distributed in this histogram?

• Symmetrically

• Skewed Right

• Skewed Left

Choose the statistical question:

• What time did you wake up this morning?

• What time do 12th graders wake up each morning during the school week?

The measure of central tendency which is commonly named as the “average”.

• mean

• median

• mode

• variance

The middle value in the list of numbers.

• mean

• median

• mode

• variance

The value that occurs most often

• median

• mean

• variance

• mode

The mean, the median and the mode of a normal distribution coincides at

• center

• left

• right

• all of the above