(d) Identify and interpret a 95% confidence interval for the mean demand and prediction in- terval for an individual demand when x4 = .20, x3 = 6.5, adver = C.

What the the estimated marginal effect at the mean?

Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 40 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that ? = 7.30 ml/kg for the distribution of blood plasma.     (a) Find a 99% confidence interval for the population mean blood plasma volume in male firefighters. What is the margin of error? (Round your answers to two decimal places.)   lower limit =______ upper limit =______ margin of error = _______   (b) What conditions are necessary for your calculations? (Select all that apply.) ? is unknown n is large the distribution of volumes is uniform the distribution of volumes is normal ? is known     (d) Find the sample size necessary for a 99% confidence level with maximal…

Consider a population that has a score of X = 15 associated with a z-score of +1.50. What does this z-score indicate about the location of X = 15? A score of X = 15 is 1.5 mean units below the standard deviation. A score of X = 15 is 1.5 mean units above the standard deviation. A score of X = 15 is 1.5 standard deviations above the mean. A score of X = 15 is 1.5 standard deviations below the mean.

Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 50 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that ? = 7.20 ml/kg for the distribution of blood plasma.

Researchers measured the percent call: Im(formula - Symptoms - wear_mask, data - some_states) of people in 25 states who 'knew someone with COVID symptoms' (ŷ) Residuals: Min 10 Median 30 мах -7.9167 -2.3306 -0.2469 2. 5020 7.3345 coefficients: and regressed this on the (Intercept) 111.0981 wear_mask Estimate std. Error t value Pr(>|t|) 10. 5423 10. 538 2.82e-10 *** -8. 375 1.94 e-08 *** -1.0419 0.1244 percent of the population frequently wearing a mask in public (x). signif. codes: 0 ***** 0.001 **** 0.01 * 0.05 '.' 0.1''1 Residual standard error: 3. 859 on 23 degrees of freedom Multiple R-squared: 0.7531, F-statistic: 70.15 on 1 and 23 DF, p-value: 1.936e-08 Adjusted R-squared: 0.7423 Which of the following represents the correct regression equation? 1) ŷ = -1.04 + 111x 2) x = 111.10 – 1.04ý 3) ŷ = 111.10 + 10.54x %3D 4) ŷ = 111.10 – 1.04x

disp hp qsec wt Use the following visualization to answer questions 2 - 4. mpg drat drat mpg qsec wt hp disp -1 -0.8 -0.6-0.4 -0.20 0.2 0.4 0.6 0.8 1

a residual is the distance between the data value in the line of best fit true or false?

1. Describe the key features of the normal curve and explain why the normal curve in real-life distributions nevermatches the model perfectly.

A linear model was fit to predict weekly Sales of frozen pizza (in pounds) from the average Price ($/unit) charged by a sample of stores in a city in 39 weeks over a three -year period. The average Sales were 63, 200 pounds (SD = 10, 670 pounds), and the correlation between Price and Sales was -0.529. If the Price in a particular week was two SD higher than the mean Price, how much pizza would you predict was sold that week?