Question

A production manager measures the lifetimes of 10 lightbulbs by leaving them all on until each one burns out. The lifetimes she measures are 568, 342, 457, 423, 398, 412, 502, 375, 493, and 450, all measured in hours. This is an example of what phase of inferential statistics?

xample of what phase of inferential statistics?

A. Probability-based inference
B. Data organization
C. Data gathering
D. Data analysis

Answer 1

C

Answer 2

you sure?

Answer 3

yes

Answer 4

thank you! i have more!

Answer 5

A production manager has measured the lifetimes of 10 toothbrushes. The lifetimes she measured are 350, 385, 388, 432, 443, 460, 469, 493, 522, and 588 hours. She calculates the mean of these numbers. What is the mean lifetime?

Answer 6

add them all and divide nby the number of numbers?

Answer 7

yes

Answer 8

When the production manager draws bar charts representing her bulb-lifetime data, this is an example of what phase of inferential statistics?

A. Probability-based inference
B. Data collection
C. Data gathering
D. Data organization and analysis

Answer 9

D

Answer 10

You test 8 automobiles and find that their mileage ratings are 25, 25, 26, 27, 30, 31, 32, and 340 mpg, arranged in order from smallest to largest. The average of these numbers is 536 ÷ 8, or 67 mpg. However, the last data value (340 mpg) seems impossibly large, and you decide that it must be due to an error in the data gathering process. Rather than doing all your measurements all over again, at considerable expense, you decide to simply ignore the "bad" value of 340 mpg. (When they do this, scientists say they are "rejecting the outliers," by ignoring unreasonable values that are nowhere close to the main cluster of data points. This procedure has some risks.) What is the mean of the remaining mileage numbers?

HUH???

Answer 11

@medisynergi22