Interpret the smoothing constant $\alpha$. What is its range?

What sums are needed to calculate the least squares estimates?

How are the least squares formulas for the slope and intercept derived?

Explain the logic of the ordinary least squares (OLS ) method.

What are the limitations of Excel’s scatter plot fitted regression?

Explain how you fit a regression to an Excel scatter plot.

Explain the difference between one-factor and two-factor ANOVA.

Below are grade point averages for 25 randomly chosen university business students during a recent semester.

Research question: Are the mean grade point averages the same for students in these four class levels?

In a one-factor ANOVA with sample sizes $n_1$ = 5, $n_2$ = 7, $n_3$ = 6, $n_4$ = 7, $n_5$ = 5, the test statistic was $F_{calc}$ = 2.447.

(a) State the hypotheses.

(b) State the degrees of freedom for the test.

(c) What is the critical value of F for $\alpha$ = .10?

(d) What is your conclusion?

(e) Write the Excel function for the $p$-value.

Using the following Excel results:

(a) What was the overall sample size?

(b) How many groups were there?

(c) Write the hypotheses.

(d) Find the critical value of F for $\alpha$ = .10.

(e) Calculate the test statistic.

(f ) Do the population means differ at $\alpha$ = .10?

Using the following Excel results:

(a) What was the overall sample size?

(b) How many groups were there?

(c) Write the hypotheses.

(d) Find the critical value of F for $\alpha$ = .05.

(e) Calculate the test statistic.

(f) Do the population means differ at $\alpha$ = .05?

An estimated regression for a random sample of observations on an assembly line is Defects = 3.2 + 0.045 Speed, where Defects is the number of defects per million parts and Speed is the number of units produced per hour. The estimated standard error is $s_e$ = 1.07. Suppose that 100 units per hour are produced and the actual (observed) defect rate is Defects = 4.4.

(a) Calculate the predicted Defects.

(b) Calculate the residual.

(c) Standardize the residual using s$_e$.

(d) Is this observation an outlier?

When is exponential smoothing most useful?

For the exponential distribution:

(a) tell how many parameters it has;

(b) indicate what the parameters represent;

(c) describe its shape; and

(d) explain when it would be used.