b) Variable Definitions and Descriptive Statistics

Which variable is the dependent variable and what are the independent variables? What do the variables mean and what are their units of measurement? Present this in a table in Word.

Present descriptive statistics for the dependent variable by using Excel to calculate the mean, median, mode and standard deviation. Present this in a table in your Word document.

Use Excel to create a histogram of your dependent variable. Copy this histogram to your Word document and comment on whether it is skewed and unimodal, bimodal or multimodal.

Use Excel to create a correlation matrix for all variables. Copy this correlation matrix to your Word document and comment on the degree of correlation among the independent variables.

Make a scatter diagram of the dependent variable and the independent quantitative variable having the highest correlation with your dependent variable.

c) Simple Linear Regression Analysis (SLR)

Perform a SLR with your dependent variable and the independent quantitative variable having the highest correlation with your dependent variable.

Use your scatter diagram from b): Place this chart on the same worksheet as where the estimated regression equation is located. Add a trend line and the estimated regression equation to the chart. Copy it to your Word document and comment on the following items:

1. What does it tell you about the relationship between the two variables? 2. State the population regression model to be estimated. 3. Describe the goodness of fit of the estimated regression line. 4. State the least-squares estimates of the slope and the intercept. 5. Give practical meanings (interpret the values) to the estimated slope and intercept.

d) Multiple Linear Regression Analysis (MLR)

Perform two different MLRs of your dependent variable against a selection of your independent variables, and use the Partial F-test to compare the two models. On the basis of this test, which of the two models is the preferred one? Comment on why this is the preferred model.

Given the correlations among the independent variables that you found earlier, are there any reasons to believe that we may have substantial multicollinearity? What does this mean? Comment on this in your Word document and, if necessary, undertake a remedy.

Please show all formulas used on excel spreadsheet

Country	Life Expectancy	People per Television	People per Physician	Female Life Expectancy	Male Life Expectancy
Argentina	70.5	4	370	74	67
Bangladesh	53.5	315	6166	53	54
Brazil	65	4	684	68	62
Canada	76.5	1.7	449	80	73
China	70	8	643	72	68
Colombia	71	5.6	1551	74	68
Egypt	60.5	15	616	61	60
Ethiopia	51.5	503	36660	53	50
France	78	2.6	403	82	74
Germany	76	2.6	346	79	73
India	57.5	44	2471	58	57
Indonesia	61	24	7427	63	59
Iran	64.5	23	2992	65	64
Italy	78.5	3.8	233	82	75
Japan	79	1.8	609	82	76
Kenya	61	96	7615	63	59
Korea, North	70	90	370	73	67
Korea, South	70	4.9	1066	73	67
Mexico	72	6.6	600	76	68
Morocco	64.5	21	4873	66	63
Myanmar (Burma)	54.5	592	3485	56	53
Pakistan	56.5	73	2364	57	56
Peru	64.5	14	1016	67	62
Philippines	64.5	8.8	1062	67	62
Poland	73	3.9	480	77	69
Romania	72	6	559	75	69
Russia	69	3.2	259	74	64
South Africa	64	11	1340	67	61
Spain	78.5	2.6	275	82	75
Sudan	53	23	12550	54	52
Taiwan	75	3.2	965	78	72
Tanzania	52.5	*	25229	55	50
Thailand	68.5	11	4883	71	66
Turkey	70	5	1189	72	68
Ukraine	70.5	3	226	75	66
United Kingdom	76	3	611	79	73
United States	75.5	1.3	404	79	72
Venezuela	74.5	5.6	576	78	71
Vietnam	65	29	3096	67	63
Zaire	54	*	23193	56	52