Conduct the appropriate hypothesis test and compute the test statistic. A company that produces fishing line undergoes random testing to see if their fishing line holds up to the advertised specifications. Currently they are producing 30-pound test line and 20 randomly selected pieces are selected to test the strength. The 20 pieces broke with an average force of 29.1 pounds and a sample standard deviation of 2 pounds. Assuming that the strength of the fishing line is normally distributed, perform the appropriate hypothesis test at a 0.05 significance level in order to determine whether there is sufficient sample evidence to conclude the fishing line breaks with an average force of less than 30 pounds.

Question 29 options:

No, because the test statistic is -2.01

Yes, because the test statistic is -2.52

Yes, because the test statistic is -2.01

No, because the test statistic is -2.52

Cannot be determined
I'm starting to hit a wall here. Can I have some guidance through this question?

Me with this assignment ! i only partially understand, so explain. also it's a work sample. at the championship bike race, steve and paula were fighting for first place. steve was 175 feet ahead of paula and had only 300 feet left to go. he was very tired and was going only 9 feet per second. paula was desperate to catch up and was going 15 feet per second. who won the bike race and by how far did she/he win?

For the word below, click on the drop-down arrows to select the root and its meaning. version

1. the manager of collins import autos believes the number of cars sold in a day (q) depends on two factors: (1) the number of hours the dealership is open (h) and (2) the number of salespersons working that day (s). after collecting data for two months (53 days), the manager estimates the following log-linear model: q 4 equation 1 a. explain, how to transform the log-linear model into linear form that can be estimated using multiple regression analysis. the computer output for the multiple regression analysis is shown below: q4 table b. how do you interpret coefficients b and c? if the dealership increases the number of salespersons by 20%, what will be the percentage increase in daily sales? c. test the overall model for statistical significance at the 5% significance level. d. what percent of the total variation in daily auto sales is explained by this equation? what could you suggest to increase this percentage? e. test the intercept for statistical significance at the 5% level of significance. if h and s both equal 0, are sales expected to be 0? explain why or why not? f. test the estimated coefficient b for statistical significance. if the dealership decreases its hours of operation by 10%, what is the expected impact on daily sales?