Applied Statistics and Software

What you will learn

Knowing test runs

Understanding non-parametric tests

Processing of assigning ranks

Understanding statistical errors

Developing cluster analysis

Description

Statistics is the discipline that deals with the synthesis, presentation, analysis and evaluation of numerical data in order to highlight proposed or assumed statistical meanings. So:

– statistics is a tool of the scientific method in science, which has several components (observation, hypothesis development, empirical data analysis, conclusion);

– variables are characteristics of reality that can take different values and are directly measurable;

– latent variables express science constructs measured indirectly by means of indicators (observed variables);

– descriptive statistics deals with the organization, synthesis, description and presentation of data;

– inferential statistics deals with the generalization of the results at the level of the population from which the sample was drawn and supports conclusions regarding the research hypotheses;


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– the dependent variables are those that are the object of the researcher’s direct interest, being measured in order to draw a conclusion;

– the independent variables represent the condition or context from which the variation in the values of the dependent variable results and are those variables that the researcher manipulates;

– the population represents the totality of information units that constitute the objective of interest of a research. As a rule, in social and human sciences the units of information represent persons;

– the sample represents a selection, based on a certain rule, of the units of information, with the aim of drawing conclusions about the population . A sample is representative when its characteristics fairly reproduce the characteristics of the population from which it was drawn. Sample representativeness is always imperfect (contains some error);

– measurement means assigning numbers or symbols to some characteristics of reality (objective or subjective) according to certain aspects (quantitative or qualitative);

– measurement levels are: nominal, ordinal, interval, ratio (they are ordered hierarchically which means that the higher scales include the properties of the lower scales). Levels are also called measurement scales. In statistical programs Measure columns contain three coding options (nominal, ordinal, scales). For the first two options (nominal and ordinal) the measurements are equivalent.

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Content

Non-parametric tests

Overview 1
Non-parametric tests

Chi-Square and binomial test

Chi-Square and binomial test
Runs and Kolmogorov-Smirnov tests

Runs and Kolmogorov-Smirnov tests

Overview 2

Mann-Whitney test and ranks

Mann-Whitney test and ranks

McNemar tests

McNemar tests

Friedman’s, Kendall’s W and Cochran ‘s Q tests

Friedman’s, Kendall’s W and Cochran ‘s Q tests

Tests for k independent samples

Overview 3
Tests for k independent samples

Statistical errors

Statistical errors

Cluster analysis

Cluster analysis

Cronbach’s Alpha coefficient

Cronbach’s Alpha coefficient

Primary tools and analyses

Overview 4
Primary tools and analyses

Distributions and assumptions

Distributions and assumptions

Statistical decision

Statistical decision