Study Guide for Exam 2 - Communication Research Methods | COM 210, Study notes of Communication

Download Study Guide for Exam 2 - Communication Research Methods | COM 210 and more Study notes Communication in PDF only on Docsity! Study Guide for Exam 2 Covers what we have done in class, the course pack explanations, and APA documentation (again). This exam will also ask you to interpret tables and figures such as what the computer produces as output. There will be some review of key material from the previous exam as well. We did NOT cover, and you will not be tested on, pages 119-123 (experiments/nonexperiments, high/low control experiments, causality, and types of research designs). Everything else, though, is fair game. Types of data (Nominal, Ordinal, Interval, Ratio) Categorical Data (two types) Nominal Data: nominal means “in name only.” The number here stands for the name. The number itself is meaningless—it is just assigned to a category, and it doesn’t matter which category comes first. The number is an arbitrary “stand in” for the name. Example: Men and women: You can assign 1 to men and 2 to women, or 2 to men and 1 to women, it doesn’t make any difference. You can report the mode, but the mean and the median are meaningless with nominal data. Ordinal Data: The represents a category—the number stands for a category. However, here order does matter, and you have to keep the numbers in the right order. Example: Many surveys as for your year in school: freshman, sophomore, junior or senior. These have to stay in the right order, because freshmen have fewer credits than sophomores, sophomores have fewer than juniors, etc. So the number you assign to juniors can’t be smaller than the number you assign to freshmen. Continuous Data Interval Data: the number means something; it doesn’t just stand for a category. The space “between” the numbers (in other words, the interval) is equal. You can meaningfully report mode, median, and mean for interval and ratio data. Example: the distance between 34 degrees and 36 degrees is the same as the distance between 76 degrees and 78 degrees. {all scales used in our COM 210 survey were interval scales. Most scales, with 5 or more responses, are considered interval scales (surveys that have you report your agreement are interval scales)} Ratio Data: the main difference between interval and ratio data is that ratio data has an absolute zero. This is a “true” zero that indicates a complete absence of that characteristic. Example: if you are asked “How many languages do you speak, aside from English?”, and you don’t speak any, the zero you write in the answer to that question is a true zero, meaning you speak 0 languages other than English. Another example is income. If you ask “How much money did you make last week?”, “zero” is a potential, accurate answer, so income in this example is ratio data. Measures of central tendency Mean: this is the arithmetic average. How to calculate Mean: mean is calculated by adding up all the scores (or numbers) and dividing by the number of scores. When you use Mean: mean is used when you want to find the average of a group of numbers. Median: this is the middle number. Half the scores (or numbers) fall above the median, and half fall below. How to calculate Median: Finding the middle number in a group of numbers, ordered low to high. When you use Median: when you want to know which number half the numbers fall below and half the numbers higher than. Mode: this is the number that occurs most often. How to calculate Mode: find the number picked most often. When you use Mode: When you want something picked, or occurring, most frequently. Measures of dispersion Measures of dispersion are ways to tell how spread out or clustered a group of numbers is. (range, standard deviation), definitions, and how to read them from a table and interpret them. Range: the range is the simplest measure of dispersion. Generally, you show the smallest number actually observed and the largest number actually observed. Examples: The range on the quiz was 3 to 10 OR Quiz scores ranged from 3 to 10. Standard Deviation (SD): the average different (deviation) between the mean and each data point, measured in the original measurement units. The SD tells you, on average, how spread out the socres are around the mean. How much different is the average score from the mean? Variance: used when comparing two things reported in different units of measurement. Positive and negative correlations What these look like on a scatterplot What does a Pearson correlation mean? What is a large versus small correlation? Significance (what does p < .05 or p > .05 mean?) What type of graph you would use for what type of analysis (t-test versus correlation) Validity and reliability recap Validity=Accuracy (different types of validity on p. 114) Reliability=Consistency (different types of reliability on p. 115) Methods: What goes into a methods section? Description of participants, measures and procedures. Results: I will provide you two tables, one for a t-test and one for a correlation, and you will need to be able to interpret the tables and produce a “results” write-up as you would for a paper. 1) What was the Research Question? 2) Overall descriptive statistics, variable number 1 (independent variable)