Learning Outcomes

Introduction to Datasets

Measuring Centre of a Dataset

Comparing Univariate Data in a Dataset

Introduction to Multivariate Data

Transformations to Achieve Linearity

Lesson Summary

To start, this module will introduce you to data exploration. You will learn about the important metrics used in measuring the centre of a data set. You will also be introduced to how transformations are used as a technique for linear and non-linear models.

Methods of Data Collection

Planning and Conducting Surveys

Planning and Conducting Experiments

To start, this module will introduce you to how samples are selected from populations and conclusions made about those populations based on the samples. The module also introduces how surveys are used as an instrument for asking questions from a selected group of people.

Diploma in AP Statistics - First Assessment

In order to pass this assessment, you will need to score 80 per cent or above. Remember, if you do not achieve the required standard after the first attempt, you can re-take the assessment until a successful outcome is achieved.

Introduction to Probability

Discrete Random Variables and their Probability Distributions

Normal Distribution

Sample Distributions

Central Limit Theorem

To start, this module will introduce you to several methods used in interpreting relative frequency. The module also covers the notion of dependence versus independence in probability and how they are used in statistics

Introduction to Estimation

Tests of Significance

Large Sample Confidence Interval for a Proportion

Test for a Mean

To start, this module will introduce you to the relationship between estimation and statistical inferences. You will learn about estimating population parameters and margin errors. You will also be introduced to the properties of the point estimator.

Diploma in AP Statistics - Second Assessment

Diploma in AP Statistics - Course Assessment

An introductory college-level course that looks at probability in data exploration and dataset characterization.

Diploma in AP Statistics

This course covers anticipating patterns involving the exploration of random phenomena using probability and simulation. It also describes data exploration as a statistical concept in data analysis where analysts use visualization and statistical techniques to describe dataset characterizations. By the end of this course, you should be ready to apply statistical reasoning in various fields of learning.

Introduction to Statistics and SPSS

Summary Statistics

Graphical Representations

Data Management

This module outlines the concepts and terminologies in data analysis and interpretation. Learn about sampling, types of variables, scales of measurement, and more. We will introduce the SPSS user interface and summary statistics for categorical and numerical variables. We will also examine graphical representations for exploratory data analysis.

Test of Hypothesis

More on Test of Hypothesis

Analysis of Variance (ANOVA)

Non-Parametric Test

This module presents the concepts of statistical data management. Learn to transform data, recode variables, make random selections, and sort data in SPSS. We will discuss how to carry out tests of hypotheses and analysis of variance (ANOVA) in SPSS. We will also consider five types of non-parametric tests and their applications in data analysis.

Correlation and Regression Analysis

More on Correlation and Regression Analysis

Binary Logistic Regression

Ordinal Data

A Case Study

This module explores correlation and regression models. We discuss the strength of associations, the correlation coefficient, and their implementation in SPSS. We consider scatterplot matrices and regression models. We also examine the multivariate analysis of variance (MANOVA), ordinal data analysis, and case studies of data analytics with SPSS.

Diploma in Data Analysis Using SPSS - Assessment

Learn how to use SPSS software to filter, analyse, interpret and visualise data in this free online diploma course.

Diploma in Data Analysis Using SPSS

Data analysis focuses on cleaning unprocessed data, processing it and visualising it with various tools and techniques. SPSS (Statistical Package for the Social Sciences) aids basic and advanced data analyses by making it easier for you to manipulate data and transform the outcome into usable information. This course shows you how to use SPSS for summary data analysis, hypothesis testing, analysis of variance, correlation and regression models.

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