Improve your Ability to Collect, Analyze and Communicate Complex Statistical Data
Statistics is an essential tool in many areas of research including psychology and the sciences. This course provides the most essential knowledge and skills required by consultants and researchers in a wide variety of disciplines. Topics covered include measures of central tendency, correlation, regression ttest, inferential statistics such as chi square and ANOVA.
Course Structure and Content
There are ten lessons in this course as outline below:
1. Introduction
 Key terms and concepts: data, variables
 Measurements of scale: nominal, ordinal, interval,ratio
 Data presentation
 Probability
 Rounding of data
 Scientific notation
 Significant figures
 Functions
 Equations
 Inequalities
 Experimental design
 The normal curve
 Data collection
 Simple, systemic, stratified and cluster random sampling
 Remaining motivated to learn statistics
2. Distributions
 Scope and nature of distributions
 Class intervals and limits
 Class boundaries
 Frequency Distribution
 Histograms
 Frequency polygons
 Normal distributions
 Other distributions
 Frequency curves
3. Measures of central tendency
 Range, percentiles, quartiles, mode, median, mean
 Variance
 Standard deviation
 Degrees of freedom
 Interquartile and semi interquartile deviations
4. The Normal curve and Percentiles and Standard Scores
 Normal distribution characteristics
 Percentiles
 Standard scores
 Z scores
 T score
 Converting standard scores to percentiles
 Area under a curve
 Tables of normal distribution
5. Correlation
 Scope and nature of Correlation
 Correlation coefficient
 Coefficient of determination
 Scatter plots
 Product movement for linear correlation coefficient
 Rank correlation
 Multiple correlation
6. Regression
 Calculating regression equation with correlation coefficient
 Least squares method
 Standard error of the estimate
7. Inferential Statistics
 Hypothesis testing
 Test for a mean
 Errors in accepting or rejecting null hypothesis
 Levels of significance
 One and two tailed tests
 Sampling theory
 Confidence intervals
8. The t Test
 Assessing statistical difference with the t test
 t Test for independent samples
 t Test for dependent (paired) samples
9. Analysis of variance
 Scope and application of ANOVA
 Factors and levels
 Hypothesis
 Calculate degrees of freedom
 Calculate sum of squares within and between groups
 Calculate mean square
 Calculate F
10. Chi square test
 Chi square goodness of fit test
 Calculate degrees of freedom
 Chi square test of independence
 Calculate expected frequencies
 Degrees of freedom
 Contingency tables
 Find expected frequencies
 Calculate degrees of freedom
Using Statistics
Collecting statistical information is the starting point for any task involving statistics; but alone, there is little point to collecting the information. It is only when statistics are organized, analyzed and communicated to others, that they really find value.
A good statistician needs to be a communicator; and there are many different tools which can be used to communicate statistical data to others. One of the most common tools is to use a graph.
Graphs are used to show proportional relationships and trends. The most commonly used types of graph are:
 Pie chart  a circle divided into sections, with each section representing a percentage of the whole
 Bar graph  vertical or horizontal bars that show a comparison between categories.
 Line graph  a line that links points plotted in relation to two axes drawn at right angles. A line graph shows trends or the change of one or more variables over time.
 Flow chart  a chart that displays the major steps and links in a process.
Some tips for preparing graphs:
 Place a simple and descriptive title directly above or below the graph.
 Use an appropriate scale, e.g. if an age group is 0 to 10 years, don’t show a scale of 0 to 20 years.
 Keep the design simple.
 Prepare a separate graph for each point.
 Tie the graph to the text, refer to it in the text, and place it as close to the text as possible.
 Limit the graphs to two or three sizes within a document, using the table outline (in two or three sizes) to create a sense of uniformity.


