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Class:MKTG 4154 - Marketing Research
Subject:Marketing
University:Virginia Polytechnic Institute And State University
Term:Fall 2014
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Five Types of Statistical Analysis 1. Descriptive 
2. Inferential
3. Differences
4. Associative 
5. Predictive
Descriptive Analysis mean, median, mode, frequency distribution, range, std. deviation

Inferential Analysis Confidence Interval, Hypothesis Test 
Differences Analysis t-test, ANOVA
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Associative Analysis correlation, chi-square test 
Predictive Analysis Regression
Parameters Represent "what we wish to know" about a population
Statistics Are used to estimate population parameters
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Statistical Inference a set of procedures in which the sample size and sample statistic are used to make an estimate of the corresponding population parameter 
Sample Statistic usually a mean or a percentage 
Standard Error the measure of variability in the sampling distribution 

= s / sq.rt. n 

=sq.rt. (p*q/n)
Confidence Interval the degree of accuracy desired by the researcher stated in the form of a range with an upper and lower boundary 
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Null Hypothesis -What you assume to be true until presented with enough evidence to reject it 

-You typically want to disprove it 

-Almost always includes an = sign 

Alternative Hypothesis The opposite of the null hypothesis 
If your hypothesis is correct... it will fall in the confidence interval (known as supported)

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 Five Types of Statistical Analysis1. Descriptive 
2. Inferential
3. Differences
4. Associative 
5. Predictive
 Descriptive Analysismean, median, mode, frequency distribution, range, std. deviation

 Inferential AnalysisConfidence Interval, Hypothesis Test 
 Differences Analysist-test, ANOVA
 Associative Analysiscorrelation, chi-square test 
 Predictive AnalysisRegression
 ParametersRepresent "what we wish to know" about a population
 StatisticsAre used to estimate population parameters
 Statistical Inferencea set of procedures in which the sample size and sample statistic are used to make an estimate of the corresponding population parameter 
 Sample Statisticusually a mean or a percentage 
 Standard Errorthe measure of variability in the sampling distribution 

= s / sq.rt. n 

=sq.rt. (p*q/n)
 Confidence Intervalthe degree of accuracy desired by the researcher stated in the form of a range with an upper and lower boundary 
 Null Hypothesis-What you assume to be true until presented with enough evidence to reject it 

-You typically want to disprove it 

-Almost always includes an = sign 

 Alternative HypothesisThe opposite of the null hypothesis 
 If your hypothesis is correct...it will fall in the confidence interval (known as supported)

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