Hello World! It is a bright and beautiful day on the Oregon coast, which is worth recording somewhere, because we are used to “grey days”. My applied statement this week is I believe in my ability to overcome every challenge that stands between me and my goals. This week I have been a superhero, impressing even myself! I really wanted to figure out the SPSS program, and I am not a pro after 3 weeks of study, but I am becoming more comfortable with the program. I spent my weekend this week studying the SPSS software. All the videos I watched last week really helped me to conquer the system.
This week I have been busy. I had to develop three new artist web pages and I am developing a business and marketing plan for a mutual fund company. Interestingly enough, my course readings make the review of the mutual fund company’s financial reporting and planning easier to understand. Additionally, I have found that SPSS is a great resource for a multitude of graphs and visual data. I am proud. I am exhausted. I am feeling prepared for week four and gear to get started.
My advice to students approaching this course, is to not consider it a ‘normal’ course. This is the most challenging course to date… and I do not say this to discourage you. Rather I hope it encourages you to touch up on your statistics and really spend time with Khan Academy prior to entering the course.
Are you already in the course and it is too late to pre-study, no worries, hit up the library. There are excellent resources and tutorials for IBMs SPSS program and how to accomplish the functions. Week 3 presents a real hurdle for some, but I believe in you and you can do this!
The focus this week will be the development of your survey, dispersion, and clean data.
In my learning I have been discussion the measures of dispersion a great deal this week. The measures of dispersion are the range, variance, and standard deviation when discussing descriptive statistics. Hanneman, Kposowa, and Riddle (2013) had discussed how dispersion conceptually relates to the linguistic understanding of diversity, variability, and difference. The range, variance, and standard deviation are ways to help the researcher identify the spread of scores among a bunch of scores.
As an example, if we were describing the length of house cats in a small town, the researcher may want to identify how much variance exists in the length of cats. Maybe most cats are 15 inches and the second largest majority are around 21 inches.
Very similarly to central tendency, the range variance and standard deviation allow the researcher to summarize a bunch of numbers or just a few numbers, and possibly a singular number in a spread of scores. Hanneman, Kposowa, and Riddle (2013) reminds the researcher that all cases do not share similar scores and variance in scores can be expected. The dispersion data is used to create a better understanding for a selection of scores. This provides the researcher the ability to look further into the data provided them.
Hanneman, R. A., Kposowa, A. J., & Riddle, M. D. (2012). Basic statistics for social research (Vol. 38). John Wiley & Sons.