Cycle tour through multivariate statistics: Part 8 Conclusion

Conclusion Based upon all the analysis performed in this paper, I conclude the following for the cycle touring dataset: As respondents get older, their cycling budget increases. To more money respondents spend the less nights per week they spend in budget accommodations. The longer tours (in both days and distance) and for tours that visit Read More …

Cycle tour through multivariate statistics: Part 7 Structured Equation Modeling

For the path analysis, I wish to determine the influences several variables have on tourAwesomeness. Typically, the hypothesis would be formulated before data is collected, but in this case, I’m working with the data I’ve got. My first step was to divide the variables into time order of their effect. I categories variables as: Demographic Read More …

Cycle tour through multivariate statistics: Part 6 Logistic Regression

Logistic Regression The research question I wish to answer using logistic regression is: which variables in the cycle touring dataset can be used to predict blogging? I ran a logistic regression with all the variables. In the block 0 variables not in the equation table, see Table 12, I noted all the variables that were Read More …

Cycle tour through multivariate statistics: Part 5 Multiple Regression

The research questions I wish to answer using multiple regression are: Which variables can be used to predict tourAwesomeness? Determine how much variance in tourAwesomeness can be accounted for by all the significant variables? Determine how much variance is tourAwesomeness can be accounted for by each significant variable after accounting for the other variables. I Read More …

Cycle tour through multivariate statistics: Part 4 Principal Component Analysis (Factor Analysis)

The research question I wish to answer using principal component analysis is: can any factors be extracted from the continuous variables with medium or high correlations? Based upon the Pearson correlation, see Table 2, the following variables have a correlation ? 0.3: Age, BudgetAccom, Budget, RideDays, TotalDays, TotalDist, and Variety; therefore, I used these variables Read More …

Cycle tour through multivariate statistics: Part 3 Bivariate Correlation

Bivariate Correlation The research question I wish to answer using bivariate correlation is: which of the continuous variables in the cycle touring dataset have a medium or strong correlation (with continuous and dichotomous variables)? For the definition of medium and high correlation, I will use the values defined by Cohen and specified in Pallant (2010, Read More …

Cycle tour through multivariate statistics: Part 2 Descriptive Statistics

Descriptive Statistics I ran a frequency distribution in order to generate the percentages for dichotomous variables. To generate the average, minimum, and maximum values for the continuous variables, I ran descriptive statistics. The descriptive statistics that I thought were interesting are: Percentage of participants from North America? (76% from North America, 24% not from North Read More …

Cycle tour through multivariate statistics: Part 1 Data Preparation

As part of my statistics course this semester, I did a survey of cycle tourists and used a variety of multivariate statistical techniques to analyze the resulting data. First off, I’d like to thank those of you who responded to the survey, special thanks to warmshowers.org, crazyguyonabike.com, travellingtwo.com and goingeast.ca, for sharing the links to Read More …

Advanced statistics in Education – Week 1

This weeks learning tips: Check out the Khan Academy for a wide variety of good quality math and science video tutorials. Save time by speeding up playback with Enounce MySpeed. One of the courses I'm taking this semester is titled Advanced Statistics in Education: Multivariate Data Techniques (EDU 7395). This is the first face-to-face classroom Read More …