Data analysis using SPSS and Excel Hans Baumgartner

Data analysis using SPSS and Excel Hans Baumgartner Smeal College of Business

Data analysis Steps in the data analysis process § Familiarize yourself with the questionnaire § Input the data and/or read the data into the program you’re planning to use § Screen the raw data carefully and correct any errors § Decide which analyses you want to perform on the cleaned data (depending on your research questions) § Report the results

Data analysis Reading the data § Download the data files from the following directory: http: //www. personal. psu. edu/jxb 14/EPL § Open the data in SPSS or Excel § Make sure that the data have been read correctly

Data analysis Screening the raw data § Check for coding errors and correct any errors □ Analyze the wtp and appeal variables § Recode variables if necessary □ The variable tix is currently coded as 1=No and 2=Yes; recode to 0=No and 1=Yes and call the resulting variable tix 01 § Pay attention to missing values □ Which variables have missing values? § Identify unusual observations □ Analyze the variable Response. Time § Assess the distribution of the variables □ Construct a histogram for the variable wtp

Data analysis Some common analysis types: Single-variable analyses § Frequencies □ How many fans chose each of the EPL teams as their favorite team? § Descriptive statistics such as means or proportions What is the maximum price that a fan is willing to pay on average to watch his or her favorite team play its biggest rival? □ What’s the proportion of fans in this sample that have season tickets? □

Data analysis Some common analysis types: Bivariate analyses § Crosstabs □ How many men and women currently have season tickets? § Comparison of means across groups □ Do men and women differ in their identification with their favorite team? § Correlation □ How strongly is team identification correlated with the success, talent, entertainment, dedication, admiration and care attributed to the favorite team?

Data analysis Some common analysis types: Multivariate analyses § Regression □ Is team identification related to the number of years someone has been supporting his or her favorite team, the distance to the home stadium, gender or age?