# Statistics: Scientific Method and Course-delivery Format

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This paper will review different styles of research design along with how different variables within research can be measured. Statistics Research Question: Within the realms of a psychological statistics class, does blended course-delivery format result in students attaining a higher grade point average when compared to face-to-face and online delivery formats? Null Hypothesis: Within the realms of a psychological statistics class, blended course-delivery format results in higher grade point averages than face-to-face and online delivery formats. Alternate Hypothesis:

Within the realms of a psychological statistics class, face-to-face course-delivery format results in higher grade point averages than blended and online delivery formats. Considering the performance of students is based on numeric averages, and the variables within the study will be the averages of students compared to each course-delivery format, the study will have a quantitative design. Quantitative design is researched defined in a numerical fashion (Usable Stats, 2013). Qualitative concerns will be the teacher of the course and how the information is taught within each format.

Another qualitative concern that may jeopardize results would be the individual student as well. How much sleep did each student obtain before class? Are there any environmental influences keeping the individuals mind away from his/her studies? Correlation Research Design: This research study design would be classified as correlation research. Correlation research is where research compares one variable against another. In this particular research design, the comparison would be student performance while under three different variables: online, blended, or face-to-face course delivery format.

Each format will be compared with the others through grade averages within the classroom. If this study were conducted on a multiple scale and geographically spread out, then one could determine the significance of the correlation among performance within each course-delivery format. Nominal Scale: To view the research on a nominal scale, the research data can be drawn from the type of class. The word nominal is derived from the root word in Latin for name (Usable Stats, 2013). The name of the class, Psychological Statistics, is the nominal measurement for this research.

When conducting this study, the study will only be measured during the course of this specific class. The results could drastically change when considering another type of class such as Quantitative Literacy as the cognitive understanding of such a collegic math class may be more optimal through a different course-delivery format. Ordinal Scale: To view the research on an ordinal scale, the research data can be drawn from the letter grade achieved from each student. Ordinal refers to the ranking order, for example A, B, C, D and F with A being the highest in ranking order and F being the lowest. Interval Scale:

To view the research on an interval scale, the research data can be drawn from the actual number average of grades within the classroom for each student. Interval scale refers to the difference between intervals being of equal distance. For instance the different from 99 to 100 is the same as the difference between 0 and 1. Ratio Scale: To view the research on a ratio scale, the research data can be drawn from the actual number average of the grades within the class for each student as well. Once the correlation is made on grade average/student performance on each type of course-delivery format, the coefficient can be set.

For instance, if the research indicates that there is a correlation between blended course-delivery format and higher grade point averages then the coefficient will be +1. 0. If there is no correlation at all the coefficient is -1. 0 with the median being 0. 0. Inferential and Descriptive Statistics: In reference to this research study, I would choose descriptive statistics. Through descriptive statistics one can use mode, mean, and median to form statistics, graphs, and charts of the central tendency of the research.

For example, if I researched 5000 students within the psychological statistics class and how each grade point average differed with each course-delivery format, I would need to find the central tendency of the grades earned to find the central point and view the spread of grades achieved by each student (Laerd Statistics, 2013). Frequency Polygon: I chose a frequency polygon to execute an example of possible results because the frequency polygon is best used in psychological quantitative research. The frequency polygon contains a bell curve as well which reflects the average/middle range of grades.

The graph shows grade point averages in correlation with number of students who achieved those grade point averages out of a sample size of 100 students. Grade Point | Frequency| 90-100| 60| 80-89| 32| 70-79| 8| 60-59| 0| References Laerd Statistics. (2013). Descriptive and Inferential Statistics. Retrieved from https://statistics. laerd. com/statistical-guides/descriptive-inferential-statistics. php Usable Stats. (2013). Fundamentals of Statistics 1: Basic Concepts :: Nominal, Ordinal, Interval and Ratio. Retrieved from http://www. usablestats. com/lessons/noir