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### BUSSTAT 208 More on descriptive statistics

Course: BUSSTAT 208, Fall 2011
School: Boise State
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Word Count: 483

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data 1 Basic analysis Essentially summarizes and communicates patterns found in the data sets Before data can be analyzed: data entry stage the creation of a computer file that holds raw data 2 Data coding Assigning codes to the possible responses for each question typically codes are numerical in large projects, a data code book may be used 3 Data matrix The coded raw data from the survey columns:...

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data 1 Basic analysis Essentially summarizes and communicates patterns found in the data sets Before data can be analyzed: data entry stage the creation of a computer file that holds raw data 2 Data coding Assigning codes to the possible responses for each question typically codes are numerical in large projects, a data code book may be used 3 Data matrix The coded raw data from the survey columns: represent answers to the questions rows: represent each respondent or case 4 Data reduction Marketing researcher faces problem of data reductionwhen confronting a data matrix. How do I condense the data matrix into a few representative measures which can help me summarize the data and convey their salient characteristics? 5 What data reduction accomplishes Summarizes the data Applies understandable conceptualizations Communicates underlying patterns Generalizes sample findings to the population 6 Types of statistical analysis used in marketing research 1. Descriptive analysis 2. Inferential analysis 3. Differences analysis 4. Associative analysis 5. Predictive analysis 7 1. Descriptive analysis Used to describe the data set in a way that a "typical" respondent would respond, reveals the general pattern of responses techniques: mean, median, mode, standard deviation, range 8 2. Inferential analysis Used to generate conclusions about the populations characteristics based on the sample data techniques: hypothesis testing: estimating true population values based on sample info 9 3. Difference analysis Used to test the difference between or among groups techniques: t-test for significant differences, analysis of variance (ANOVA) 10 4. Associative analysis Used to determine systematic among relationships variables including if and how two variables are related techniques: cross-tabulations and correlations 11 5. Predictive analysis Used to help the marketing researcher make predictions or forecasts about future events techniques: regression analysis, time series analysis 12 Measures of central tendency Goal: to report a single piece of information that describes the most typical response to a given question mean, median, mode 13 Mode The value in a string of numbers that occurs MOST often used with nominal scales 14 Median Expresses the value that lies in the middle of an ordered set of values used with ordinal scales 15 Mean The average value characterizing a set of numbers used with interval and ratio scales 16 Measures of variability Depict the "typical" difference between the values in a set of values frequency/percentage distribution, cumulative percentage distribution, standard deviation, range 17 Frequency/percentage distribution A tabulation of the number of times that each value appears in a particular set of values often represented by bar charts used with nominal scales 18 Range Identifies the distance between the minimum and the maximum value in an ordered set of values 19 Standard deviation The SD indicates the degree of variation in the values translated into a normal distribution SD are standardized units that express how much of the area under the curve lies within the limits expressed: +/- 1.96 SD = 95% +/- 2.58 SD = 99% 20 When to use a particular descriptive measure for each type of scale Type of scale Nominal: Mode, frequency distribution Ordinal: Median, cumulative percentage distribution Interval/ratio: Mean, SD, range
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