The analysis of the data from the study of Barnes & Noble stores is in two stages, the descriptive study and inferential statistical study. Initially, the Team will distribute and collect the questionnaires. The use of classification will summarize the data and express it in the tabular form for better understanding of the data. For example, if the questionnaires consist of information from males and females, the data is putinto two categories and expressed in a table form. A proper graphical method can display the data summation. As an example, the display of information can be in a pie chart or simple bar chart of different categories like people who prefer to read electronic books and people who prefer to read hard copy books. Finally, a proper statistical hypothesis testing method can answer the research questions in the questionnaire. In the Barnes & Noble case study, the hypothesis test that proportion of people who prefer to read the electronic copy of books is larger than the proportion of people who prefer to read hard copy books. The hypothesis test consists of equality of proportions of two populations. The hypothesis test can assist in determining if the emergence of electronic copy of books is reducing the prices of hard bound and paperback books.
Analyzing the Data
The selection of the analysis is based on two things: the way the hypothesis is stated in statistical language and the level of measurement of the variable. The Hypothesis
The way the researcher states the hypothesis makes a difference in the data analysis. Here are three null hypothesis examples: (1) Variable A does not relate to Variable B, (2) Variable A does not predict to Variable B, (3) There are no differences on Variable A by Variable B. (1) tends to be stated in correlation or chi-square language, (2) in regression language, and (3) in ANOVA or perhaps Mann-Whitney language. How is one to choose the precise data analysis? It...
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