There are approximately one billion smartphone users in the world today. in the united states, the ages of smartphone users between 13 to 55 approximately follow a normal distribution with approximate mean and standard deviation of 37 years and 8 years, respectively. using the 68-95-99.7 rule, what percent of smartphone users are between the ages of 29 and 45?

Martha has a deck of cards. she has lost some of the cards, and now the deck only contains nine spades, eleven diamonds, eight clubs, and twelve hearts. martha predicts that whenever she draws a card from the deck without looking, she will draw a club one-fifth of the time. which activity would best allow martha to test her prediction? a. randomly draw a card from the box and see if it is a club. b. randomly draw a card. then, continue to draw another card until all eight clubs are drawn. c. randomly draw and replace a card 120 times. then, observe how close to 30 times a club is drawn. d. randomly draw and replace a card 100 times. then, observe how close to 20 times a club is drawn.

Solve the problem by making up an equation. a man could arrive on time for an appointment if he drove the car at 40 mph; however, since he left the house 15 minutes late, he drove the car at 50 mph and arrive 3 minutes early for the appointment. how far from his house was his appointment?

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?