Intro Stats, Lec 23B, Review Chi-Square Test, SS Regression formulas, Use XL Miner for Regression

(0:00) More comments about chi-squared distributions and tests.
(0:34) The formula for df in two-way tables and the nature of chi-squared graphs based on df.
(2:14) For two-way tables with r = 2 rows and c = 2 columns, the value of chi-squared is the square of the z-statistic for comparing two population proportions (of "successes").
(2:45) Calculating the P-value (given the X^2 value and df) with =CHITEST on Excel (or =CHIDIST...which is what I ended up doing by accident) and calculating the X^2 value (given the P-value and df) with =CHIINV.
(5:45) Goals related to regression for Lec 23B.
(6:33) Review use SS formulas for regression on a spreadsheet to find the correlation and slope of the regression line for a homework problem.
(16:11) Find the y-intercept.
(17:03) Finding the slope and intercept using an "add-on" for the spreadsheet...the most important method for doing inference.
(17:20) This example is not really the best context to use inferential regression methods, but we'll do it anyway just to illustrate how to get the output.
(18:19) Installing the XL Miner Analysis Toolpak "add-on".
(19:59) Using the XL Miner Analysis Toolpak for Linear Regression (step-by-step method).
(22:27) The regression summary output.
(22:55) Finding the slope, intercept, and correlation (will also find r^2 and the "regression standard error").
(23:58) This output will ultimately be good for doing inference from a sample to a population.
(24:48) This is part of a homework exercise.
(25:05) You should also be able to use this output to find the regression standard error s.
(26:05) This is an estimate for a standard deviation that is in the regression model (which models the variability in the y values for any given x value).