The following linear trend equation is used to forecast annual sales in thousands of dollars. It is based on one-year periods of time series data with t = 0 in 2013. Forecast annual sales for 2020. Y' = 37 + 0.625t.
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- Use the table of values you made in part 4 of the example to find the limiting value of the average rate of change in velocity.Match the differential EQ to the graphThe following equation summarizes the trend portion of quarterly sales of condominiums over a long cycle. Sales also exhibit seasonal variations. Using the information given, prepare a forecast of sales for each quarter of next year (not this year), and the first quarter of the year following that. Ft = 30 – 5.5t + 2.5t2 Where Ft = Unit Sales t = 0 at, the first quarter of this year Quarter Relative 1 1.1 2 1.0 3 0.7 4 1.2
- Fit a linear-regression model relating annual inci- dence of diabetes to time period. (For this purpose, score the time period as 1 if 1970−1974, 2 if 1975−1979, . . . , 5 if 1990−1994.)With respect to regression, the ___________ will increase anytime you increase the number of observations unless each observation has a residual equal to zero.Use the table to estimate the rate of change of y at the specified value of x. X=1
- Because of the popularity and power of smartphones, demand for wireless communication is growing rapidly. Suppose monthly global data traffic is predicted to be 4.5e0.573x petabytes, where x is the number of years since 2015. Find the relative growth rate in any year x.Monthly sales have been found to follow a linear trend of y = 10 + 8x, where y is the number of items sold and x is the number of the month. Monthly deviations from the trend have been calculated and follow an additive model. In month 12, the seasonal variation is estimated to be -6. What is the forecasted number of items to be sold in month 12?The average levels of particulate matter (PM2.5) a key cause of adverse health. Effects associated with air pollution have decreased in Toronto from 8.7 μg/m3 in 2014 to 7.0 in 2016. Assuming this trend continues as a linear relationship, what would we expect the levels of PM2.5 to be in the year 2022?
- A value of r close to −1 suggests a strong _______ linear relationship between the variables.The image shows the estimation of the model with quarterly car sales in the U.S. from 1975 to 1990. Based on the parameter estimates, what is the predicted effect of a 10% increase in price on the number of cars sold? What would be the effect of that price increase on the value of car sales?The following measurements correspond to air velocity and the evaporation coefficient of burned fuel droplets in a boost engine. regression equation isy =0.0692+0.0038X A) find 95% prediction limits for the evaporation coefficient, when the air speed is 190 cm / s. B) Suppose that the linear relationship continues beyond the range of experimentation and finds the 95% prediction limits for an observation of the evaporation coefficient when the air velocity is 450 cm / s.