Importance of Business Analytics and Using SPSS

Workshop - Class 1, 2

The class started by installing all the required software for using SPSS 15 tool. I was very excited about it as I had heard about it during Marketing Research Sessions and its important in Marketing was significant.


Initially we were explained the importance of SPSS and how Business Intelligence helped Marketeers to make critical decision accessing right information. The information available to us using initial Market Research Conducted using various techniques like Survey, Interviews, Observation, Questionnaires etc.

The data available can be actually categorized and combined in various ways to evaluate a hypothesis.

We learned about two different technique or Data analytics technique :

1. Frequency
2. Cross Tabs

FREQUENCIES can produce

• Tables that show
• all values that occur for a specified variable
• how frequently the values occur
• the percentage of times they occur, based on
• the total number of cases
• only cases with valid data for the variable
• Any statistic from this list
• MEAN
• SEMEAN
• MEDIAN
• MINIMUM
• MAXIMUM
• RANGE
• Graphs
• bar charts -- for discrete variables
• histograms -- for continuous variables

CROSSTABS

Crosstabs is an SPSS procedure that cross-tabulates two variables, thus displaying their relationship in tabular form. In contrast to Frequencies, which summarizes information about one variable, Crosstabs generates information about bivariate relationships.

Crosstabs creates a table that contains a cell for every combination of categories in the two variables.

• Inside each cell is the number of cases that fit that particular combination of responses.
• SPSS can also report the row, column, and total percentages for each cell of the table.

Because Crosstabs creates a row for each value in one variable and a column for each value in the other, the procedure is not suitable for continuous variables that assume many values. Crosstabs is designed for discretevariables--usually those measured on nominal or ordinal scales.
Crosstabs are usually presented with the independent variable across the top and the dependent along the side.


We worked on Sample file called Retail.sav which was based on data collected for a retail store chain covering 4 different stores and consumers satisfaction levels. We grouped the available data using cross tabs to evaluate a null hypothesis and then determing Chi square value.


Testing statistical significance using chi-square

• Chi-square tests for statistical independence between two variables
• The variables may be nominal level or higher, but it is best suited for discrete variables with limited categories.
• Chi-square is sensitive to any departure from chance relationship
• Strictly speaking, chi-square is only a test of significance, not a measure of a relationship between variables

• Consider the relationship between two discrete variables from the 2000 National Election Study
• Feelings about the Bible is the dependent variable
• Region of the country is the independent variable

Interpretation of chi-square

• The magnitude of the chi-square value must be judged against a table of values of the chi-square distribution:
• One must enter this table using the appropriate degrees of freedom: calculated according to the size of the table:
• X2 degrees of freedom = df
• = (rows - 1) (columns - 1)
• = (3 - 1) (6 - 1)
• = 2 x 5 = 10.
• Given the same degrees of freedom, the larger the chi-square value, the more "significant" it is.
• The entries in the chi-square table for a given chi-square are matched with "alpha" levels at specified levels of significance, e.g., .050 or .010 or .001
• A chi-square as large as 75 for 10 degrees of freedom would be expected by chance fewer than 1 time in 1000.

Submitted by:-
Ankit Agarwal
12070
Marketing