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Presentation transcript:

*Bring Money for Yearbook! Using Excell *Bring Money for Yearbook!

DATA Analysis (Windows 97) Go to Tools Click on “Add ins” Check 1st 2 It will now be found under Tools

DATA Analysis (Vista) Go to Tools Click on “Add ins” Check 1st 2 It will now be found under Tools

Put independent variable in column A. A study of nutrition in developing countries collected data from the Egyptian village of Nahya. Here are the mean weights (in kg) for 170 infants in Nahya who were weighed each month during their first year of life: Age (mths) Weight (kg) 1 4.3 2 5.1 3 5.7 4 6.3 5 6.8 6 7.1 7 7.2 8 9 10 11 7.5 12 7.8 Put independent variable in column A. Put dependent variable in column B. Go to Data Analysis – to Regression Hightlight B column for y-range. Hightlight A column for x-range Click on labels (if you included them) Click on output – click space to put it If you want the normal probability plot, click on it.

Regression Statistics What you get! SUMMARY OUTPUT Regression Statistics Multiple R 0.906552235 R Square 0.821836955 Adjusted R Square 0.80402065 Standard Error 0.470339361 Observations 12

ANOVA df SS MS F Significance F Regression 1 10.20448 46.12836 4.79E-05 Residual 10 2.212191 0.221219 Total 11 12.41667

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 4.88030303 0.289474 16.85922 1.13E-08 4.235315 5.525291 Age (mths) 0.267132867 0.039332 6.791786 4.79E-05 0.179496 0.354769

Scatter plot with regression line: Click on Chart wizard Scatter(xy) 1st one click Next Highlight Data Range (do not include labels) & press next Type in labels for x & y Press Next & Finish To get line – click on point & press add trendline

Normal Probability Plots Used to determine if the data is approximately normal If it appears to be a straight line – then it’s approximately normal

Find equation, r2, se for the data below comparing the intensity of a baby’s cry & their IQ. ANOVA df SS MS F Significance F Regression 1 2895.524 20.28253 0.001993 Residual 8 1142.076 142.7595 Total 9 4037.6 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 74.26985 10.0478 7.391653 7.68E-05 51.09958 97.44012 Crying 2.604357 0.578282 4.503613 1.270837 3.937877

Residual Plot Looking for no – pattern in order for it to be a good linear model Click on residual plot when doing the regression to see it.

Homework Worksheet