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What kind of data we are dealing with? Whether our data follow the normal distribution or not? What is the aim of the study?
3:14 14:59 Suggested clip CPD Webinar: Choosing the Right Statistical Test and Using the YouTubeStart of suggested client of suggested clip CPD Webinar: Choosing the Right Statistical Test and Using the
What is meant by a statistical test? A statistical test provides a mechanism for making quantitative decisions about a process or processes. The intent is to determine whether there is enough evidence to “reject” a conjecture or hypothesis about the process. The conjecture is called the null hypothesis.
Relationship questions with two categorical variables can be examined with a chi-square test. Typically, linear, ordinal, or multinomial regressions are the appropriate statistical analyses to use when the outcome variables are interval, ordinal, or categorical-level variables, respectively.
Choosing the Right Statistic. [01:19] What question type do you want to answer? [02:10] Overview of Common Statistical Analyses. [04:51] Identify & define your variables. [11:27] Draw a diagram of your design. [19:48] Determine need for parametric or non-parametric test. [26:36] Make the final decision. [31:32]
Two types of statistical methods are used in analyzing data: descriptive statistics and inferential statistics. Descriptive statistics are used to synopsize data from a sample exercising the mean or standard deviation. Inferential statistics are used when data is viewed as a subclass of a specific population.
Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation).
Definition. Statistical methods are mathematical formulas, models, and techniques that are used in statistical analysis of raw research data. The application of statistical methods extracts information from research data and provides different ways to assess the robustness of research outputs.

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