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Rise above the mean with statistics!

Strenghten your career with this course in Statistics. If you want to develop scientifically-based research studies, this is your starting point. Learn how to interpret data sets, and how to prove your point based on scientifically proven methods

This course provides the most essential knowledge and skills required by consultants and researchers in a wide variety of disciplines. This course assumes a basic knowledge of Statistics, at least to the level covered by our Research Project I course

Course Details

If you are doing the course full time you can complete it in 6 weeks, if you are studying part time then it will take 3-6 months on average to complete the course. Your course will expire after 1 year. You can start the course at any time as it is a self-paced online course.

Course Outline

There are 10 lessons in this course:

Key terms and concepts: data, variables
Measurements of scale: nominal, ordinal, interval,ratio
Data presentation
Rounding of data
Scientific notation
Significant figures
Experimental design
The normal curve
Data collection
Simple, systemic, stratified and cluster random sampling
Remaining motivated to learn statistics

Scope and nature of distributions
Class intervals and limits
Class boundaries
Frequency Distribution
Frequency polygons
Normal distributions
Other distributions
Frequency curves

3.Measures of central tendency
Range, percentiles, quartiles, mode, median, mean
Standard deviation
Degrees of freedom
Interquartile and semi interquartile deviations

4.The Normal curve and Percentiles and Standard Scores
Normal distribution characteristics
Standard scores
Z scores
T score
Converting standard scores to percentiles
Area under a curve
Tables of normal distribution

Scope and nature of Correlation
Correlation coefficient
Cooeficient of determination
Scatter plots
Product movement forlinear correlation coefficient
Rank correlation
Multiple correlation

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
Test for independant samples
Test for dependant (paired) samples

9.Analysis of variance
Scope and application of ANOVA
Factors and levels
Calculate degrees of freedon
Calculate sum of squares within and between groups
Calculate mean square
Calculate F

10.Chi square test
Chi quare goodness of fit test
Calculate degrees of freedom
Chi square test of independance
Calculate expected frquencies
Degrees of freedon
Contingency tables
Find expected frequencies
Calculate degrees of freedom


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