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

Multiplicity in hypothesis testing: where more than one hypothesis is tested, the significance level of the combined tests is not equal to the nominal significance level of the individual test (related term – false discover rate). Multiple regression : a statistical tool used to develop a self-weighing estimating equation that predicts values for a dependent variable from the values of independent variables; controls confounding variables to better evaluate the contribution of their variables; tests and explains a causal theory. Multivariate analysis of variance (MANOVA): assesses the relationship between two or more dependent variables and classificatory variables or factors; frequently used to test differences among related samples.

Multivariate Data : A set of measurements of several variables per individual. For example, the coach records height, weight, and the number of sit-ups for each athlete.

Nonparametric tests: significance tests for data derived from nominal and ordinal scales.

Nonprobability sampling: a procedure in which each population element does NOT have a known nonzero chance of being included; no attempt is made to generate a statistically represented sample.

Nonresponse: the difference between the “invited” sample sought and those obtained.

Nonresponsive rate: The rate is a fraction of the number of non-responders divided by the number of people invited to participate. If the nonresponsive rate is high, the survey suffers from a large nonresponse bias.

Normal Curve : The normal curve is often called the bell curve. The normal curve is symmetric.

Normal distribution: A normal distribution, called the "bell curve" or Gaussian Distribution, is a continuous probability distribution that is symmetrical. This is the standard comparison for describing distributions of sample data. Note that in a normal distribution, the mean will be equal to both the median and the mode! Null hypothesis (H 0 ): in hypothesis testing, the hypothesis we wish to falsify based on the data. The null hypothesis typically has wording like “no effect” or “no difference” and data, like evidence in a courtroom, must be gathered to disprove it. (Quiz) Observational Study: In an observational study , the person carrying out the study does not determine who will be in what groups. Additionally, the purpose of an observational study is to collect data that will allow you to learn about a single population or about how two or more populations will differ. Observational studies can be retrospective (backward-looking) and prospective (forward-looking). In an observational study, it is important to obtain a sample that represents the population. Do not use an observational study to draw a cause-and-effect conclusion. Cause-and-effect belongs with an experiment.

One-tailed test: a test of a null hypothesis that assumes the sample parameter is not the same as the population statistic, but that the difference is only in one direction.

Ordinal value: a variable where values have a natural order like short, medium, long, cold, warm, hot.

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