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DATA ANALYSIS I MKT525. Plan of analysis What decision must be made? What are research objectives? What do you have to know to reach those objectives?

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Presentation on theme: "DATA ANALYSIS I MKT525. Plan of analysis What decision must be made? What are research objectives? What do you have to know to reach those objectives?"— Presentation transcript:

1 DATA ANALYSIS I MKT525

2 Plan of analysis What decision must be made? What are research objectives? What do you have to know to reach those objectives? Now create plan of analysis

3 SELECTING DATA ANALYSIS TECHNIQUE How many variables will be analyzed at a time? –One variable - univariate analysis –Two variables - bivariate analysis –More than two variables - multivariate analysis

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5 Descriptive Measures Central tendency –Mode –Median –Mean Some Dispersion measures –Range –Standard deviation

6 Data Set

7 Inferential Statistics Goal = make inferences about population from sample results Mean of sample usually not = population mean Mean of sampling distribution estimates population mean Variance of sampling distribution depends on population variance, sample size, sample design

8 Inferential Statistics -2 We only have one sample We can say, based on sample, and with a certain degree of confidence, population mean falls within a certain range of values. Confidence level Standard error of the mean Confidence interval

9 Inferential Statistics-3 Hypothesis –Null hypothesis = Ho –Alternative hypothesis = H 1 If Ho not rejected, no action taken that is different from current policy - status quo. If Ho rejected, action taken which is different from current policy.

10 Type I and Type II Errors Type I error: Reject Ho when it is really true. –Probability = alpha = level of statistical significance Type II error: Do not reject Ho when it is really false. –Probability = beta - more difficult to control. Consider which error is more important to keep low.

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12 Issue 1: is sample mean different from a criterion mean? t = sample mean - criterion mean standard error of mean What is sample? Population? What is null hypothesis? Alternative? What is conclusion?

13 Issue 2: Is a sample proportion different from a criterion proportion? z = sample proportion - criterion proportion standard error of proportion s.e. of prop. = square root of: p(1-p) n What is sample? Population? What is null hypothesis? Alternative? What is conclusion?

14 Issue 3: Is a frequency distribution different from a criterion distribution? Chi square = Sum (observed - expected) 2 expected What is sample? Population? What is null hypothesis? Alternative? What is conclusion?


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