Tourism Research Seminar for Tourism and Hospitality - Data Analysis Assignment
Download the Bed and Breakfast Traveler Survey dataset with the accompanying survey and Codebook. Complete the questions below using SPSS for your data analysis. You can answer the questions right on this sheet and upload it into Moodle, or you can use a separate Word file to submit your answers. Do not email your files. Do not send your data or output files from SPSS or Excel. Send only a Word file with your answers. When you are finished this exercise, submit your file by uploading it into the assignment space in Moodle. Good luck.
1) What type of level of measurement (data scale) (Hint: See Module 4 - Slide 11)
a) Q1) OFTEN
b) Q2) LONG
c) Q4) PROV
d) Q7-5) OVERALL
e) Q14) AGE
2) Based on the level of data measurement used for each pair of variables below, what statistical tests would you use to perform the following bivariate analyses?
a) INCOME (Independent variable) by PEGGY (Dependent variable)
b) GENDER (Independent variable) by OFTEN (Dependent Variable)
c) OFTEN (Independent variable) by CLEAN
d) GENDER (Independent variable) by GUIDE (Dependent variable)
e) OVERALL (Independent variable) by AMBIENCE (Dependent variable)
3) What would the hypotheses be that you would be testing for the following relationships? Write out both the null and alternate (research) hypotheses for each.
a) INCOME (Independent variable) by OFTEN (Dependent variable)
b) GENDER (Independent variable) by TNS (Dependent variable)
c) SPEND (Independent variable) by OVERALL (Dependent variable)
d) AGE (Independent variable) by CLEAN (Dependent variable)
e) INCOME (Independent variable) by SPEND (Dependent variable)
4) Run frequencies for all categorical variables (nominal or ordinal level) and descriptive statistics for all continuous variables (interval or ratio level). (Hint: See Module 9). Then answer the following questions:
a) How many traveled alone in their last B&B trip? (Report both number and percentage)
b) What is the modal response (mode) for the amount spent nightly for the B&B room?
c) Which of the scaled questions had the highest average rating?
d) What percentage of respondents had incomes of $150,000 or more?
e) Interpret the income and age results using the cumulative percentage.
f) Write up the results of for any two of the demographic variables. Use both text and a graph or table in your write-up. Do not cut and paste tables from SPSS into your write-up. Use everyday language in your write-up so that managers who are not familiar with research or statistics would be able to understand your research findings.
5) What is the 95% confidence interval for each of the following variables?
(Hint: See Module 9)
a) OFTEN
b) STAYED (yes response only)
c) PROV (Nova Scotia visits only)
d) FRIEND
e) WILL (yes response only)
f) TIDAL (yes response only)
6) Conduct a crosstab and chi-square analysis for the following sets of variables, then explain whether they are statistically significant and why or why not. If the test is statistically significant describe the nature of the association between the variables.
(Hint: See Module 10-Slides 3-6)
a) GENDER (Independent) by TNS (Dependent)
b) AGE (Independent) by TSN (Dependent)
c) GENDER (Independent) by GUIDE(Dependent)
d) AGE (Independent) by GUIDE (Dependent)
e) INCOME (Independent) by GUIDE (Dependent)
f) Write up the results for two of the chi-square tests that you ran for this question. Do not cut and paste any of the SPSS tables into your write-up. Use both text and graphs and/or tables in your write-up. Use everyday language in your write-up so that managers who are not familiar with research or statistics would be able to understand your research findings.
7) Conduct a significance test for the following sets of variables, then explain whether or not they are statistically significant. If the test is statistically significant describe the nature of the relationship between the two variables. (Hint: See Module 10 - Slides 7-12)
a) Independent Samples t-test for GENDER (Independent) by OFTEN (Dependent) (5 points)
b) Paired Samples t-test for AMBIENCE by OVERALL
c) Write up the results for both tests using text and graphs and/or tables. Do not cut and paste any of the SPSS tables into your write-up. Use everyday language in your write-up so that managers who are not familiar with research or statistics would be able to understand your research findings.
8) Conduct an analysis of variance (ANOVA) for the following sets of variables, and then explain whether or not they are statistically significant. If the test is statistically significant describe the nature of the relationship between the two variables. (Hint: See Module 10 - Slides 13-18).
a) PROV (Independent) by CLEAN (Dependent)
b) PROV (Independent) by FOOD (Dependent)
c) PROV (Independent) by AMBIENCE (Dependent)
d) PROV (Independent) by OVERALL (Dependent)
e) Write up the results of any two of these tests. Use both text and tables and/or graphs in your write-up. Do not cut and paste any tables from SPSS into your write-up. Use everyday language in your write-up so that managers who are not familiar with research or statistics would be able to understand your research findings.
9) a) Run a correlation analysis for OFTEN by FRIEND, then explain whether or not the correlation is statistically significant and if it is, explain the nature of the relationship. (Hint: See Module 10 - 19-23).
b) Write up the results of your correlation analysis. If it is statistically significant include a line graph in your write-up. Do not cut and paste any tables from SPSS into your write-up and remember to use everyday language.
11) a) Run a regression analysis for FRIEND (Independent) by OFTEN (Dependent).
b) Write up the results of your regression analysis in everyday language. Do not cut and paste tables from SPSS into your write-up. Explain whether or not the regression is statistically significant. If it is statistically significant, describe the nature of the relationship (positive, inverse, etc.) and explain how much a how a 1-unit increase in FRIEND would impact the OFTEN (number of visits).
c) If your analysis is statistically significant show the relationship in a graph.