2022 Introduction to Statistics in Research Mitchell 2nd ed

I N T R O T O R E S E A R C H : D A T A V I S U A L I Z A T I O N & C O M M O N S T A T T E S T S

Terms and Definitions In effect, this is an abbreviated glossary of terms. Please take some time to read through them. There is a much broader list of terms available with a simple search on the internet, but sometimes you just need the foundational terms defined in simple language to get you started. These are placed in alphabetical order for your convenience with some images for visual learners. Other terms will be presented in examples that are not presented here so you get a richer context. Alternative Hypothesis: Often the research question and varies depending on whether a one-tailed or two tailed text For example, the alternative hypothesis would look like one of the following: μ 1 - μ 2 >0, μ 1 - μ 2 <0 (both of these are one- tailed) and μ 1 - μ 2 ≠0 (two -tailed)

Analysis of Variance (ANOVA): tests the null hypothesis that the means of several independent populations are equal.

Bimodal: Two modes. The histogram below illustrates a bimodal distribution.

Table 34:Example of a bimodal distribution

Binomial Distribution : a probability model for a discrete outcome (as opposed to a continuous distribution) – such as the normal distribution. There are four requirements – 1. The number of observations (n) is fixed. 2. Observations are independent of each other. 3. Each observation is either success or failure. 4. The replication is independent, meaning the probability of “success” does not influence the probability of success in another case. Example of Binomial Distribution

Bivariate: Two variables (like two measurements of an individual, i.e. height and weight). These are considered a pair of numbers for each individual.

Box plot: a visual image of the variables distribution location, spread, shape, tail length, and outliers (also called box and whisker plot).

Categorical Variable: a variable that has two or more categories, but no intrinsic ordering. (i.e., hair color has several categories (brown, blonde, red, etc.).

Causation, causal relationship: two values are causally related if the change in the value of one causes the other to change (a good example is “hours worked” and “income earned”). We sometimes equate this to cause and effect. (do not confuse causation with correlation) Central Limit Theorem (CLT): Textbook definition: The theorem states that if you have a population with a mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed . Understandable Definition: Given a sufficiently large sample size, the sampling distribution of the mean

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