Suppose you were going to create your own study to examine what course-delivery format (online, blended, or face-to-face) leads to the best performance in a psychological statistics class. In a paper identify the following for your study:

* What is your research question?
* What is your hypothesis (both null and alternate)?
* Is this a qualitative or quantitative design and why?
* Is this a descriptive, correlational or experimental design and why?
* What would be an example of a variable for this study that could be measured on a nominal scale? Ordinal scale? Interval scale? Ratio scale?
* Once you have collected your data, would you use inferential or descriptive statistics and why?
* Create a sample frequency distribution for one of the variables. Choose either a simple or grouped frequency distribution and explain your choice.

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Research Question: What course-delivery format (online, blended, or face-to-face) leads to the best performance in a psychological statistics class?

Hypothesis:
Null Hypothesis (H0): There is no significant difference in performance among students in different course-delivery formats.
Alternate Hypothesis (HA): There is a significant difference in performance among students in different course-delivery formats.

Design:
This study would use a quantitative design. Quantitative research involves collecting numerical data to analyze and draw conclusions.

This study would use an experimental design. An experiment allows the researcher to manipulate the independent variable (course-delivery format) and observe its effects on the dependent variable (performance in psychological statistics class). It provides the opportunity to establish cause-and-effect relationships.

Variable Examples:
- Nominal Scale: A nominal variable for this study could be the course-delivery format, with categories such as "Online," "Blended," and "Face-to-Face." These categories are distinct and non-ordered.
- Ordinal Scale: An ordinal variable could be students' self-reported levels of satisfaction with the course-delivery format on a Likert scale (e.g., "Very Dissatisfied," "Dissatisfied," "Neutral," "Satisfied," "Very Satisfied"). These categories have a natural order but not necessarily equal intervals.
- Interval Scale: An interval variable could be the test scores of students. The intervals between scores are equal, but there is no true zero point.
- Ratio Scale: A ratio variable example could be the number of hours spent studying for the course. It has equal intervals between values and an absolute zero, indicating no study time.

Data Analysis:
Once the data is collected, inferential statistics would be used. Inferential statistics allows the researcher to make inferences and draw conclusions about the population based on the sample data. This will help determine if there is a significant difference in performance between different course-delivery formats.

Frequency Distribution:
To create a sample frequency distribution, let's consider the variable "Test Scores." Assuming the range of scores is from 0 to 100, a grouped frequency distribution could be created with intervals such as 0-20, 21-40, 41-60, 61-80, and 81-100. This choice is made when the data range is large, and grouping the scores into intervals provides a clearer overview of the distribution, especially if it is skewed.