2. MEDIATED MOOCS Introduction to descriptive statistics
San Jose State University (via Udacity)
Prof Jenny Roberts
Institute for Open and Distance Learning (IODL)
University of South Africa (Unisa)

3. Descriptive Statistics
This course will teach you the basic terms and concepts in statistics as well as guide you through introductory probability.
Statistics is an important field of math that is used to analyse, interpret, and predict outcomes from data. Descriptive statistics will teach you the basic concepts used to describe data. This is a great beginner course for those interested in Data Science, Economics, Psychology, Machine Learning, Sports analytics and just about any other field

4. Programme Lesson Topic Date of mediated support Content 1
Introduction to research methods
14 March
Introduction to statistical study methods 2
Visualising data
Create and interpret histograms, bar charts and frequency plots 3
Central tendency
10 May
Mean, median and mode 4
Variability
Range and standard deviations
Interquartile range 5
Standardising
28 June
Convert distributions into normal distributions using the z-score 6
Normal distribution
Compute probabilities
Use of Z-table 7
Sampling distributions
Apply concepts of probability and normalisation to data sets

5. Instructions
Log onto
Register – They require your address, your full name as well as a password
Click – GO TO CLASS to start
Click – START FREE COURSE

6. Some common concepts Constructs Independent and dependant variables
Population
Sample
Frequency tables
Relative frequency
Percentages
Histogram
Bar chart

7. CONSTRUCTS Objective measurement of a subjective phenomena
Some attributes can be measured directly e.g. height, weight etc.
In the behavioral and social sciences, we usually must use more indirect ways to measure constructs, so we develop a number of items to assess the construct e.g. Depression – use a scale which measure depression or a happiness scale to measure levels of happiness
The personal characteristic to be assessed is called a construct. This personal attribute cannot be directly measure (as in height and weight) but can be assessed by using a number of indicators
In this MOOC constructs are used with reference to the behavioral and social sciences

8. Independent and dependent variables
A variable is anything that can be measured
Dependent variable – value depends on the variables that are being manipulated e.g. exam results are dependent on time spent studying. In this case the dependent variable is exam results (which was are not manipulating at all) and time spend studying is the independent variable as this can be changed in order to test its outcome on the exam results
Independent variable is also called the predictor variable
Dependent variable also know as the outcome variable

9. Population and sample
The POPULATION are all members of a defined group that we are studying.
A sample is a part of the population
The population is the broader group of people to whom you intend to generalise the results of your study.
Your sample is a subset of your population

10. Frequency tables
Frequency tells you how often something occurs. The frequency of an observation in statistics tells you the number of times the observation occurs in the data. For example, in the following list of numbers, the frequency of the number 9 is 5 (because it occurs 5 times):
1, 2, 3, 4, 6, 9, 9, 8, 5, 1, 1, 9, 9, 0, 6, 9.
Number
Count
frequency
Relative frequency
Percentage 1
1/16=0.06
1/16*100=6.25
111 3
3/16=0.19
3/16*100=18.75 2 4 5 6 11
2/16=0.13
2/16*100=12.5 7 8 9
11111
5/16=0.32
5/16*100=31.25
Total ∑ 16
16/16=1
16/16*100=100

11. Visualising data Scatter charts/Bar charts/Histograms
1, 2, 3, 4, 6, 9, 9, 8, 5, 1, 1, 9, 9, 0, 6, 9.

12. Scatter plots score frequency Relative frequency 2 0.02 1 4 0.04 72
0.02 1 4
0.04 7
0.07 3 5
0.05 12
0.12 15
0.15 6 20
0.2 25
0.25 8 9 10
0.1
total
100
Data: Test scores out of 10 for 100 students

13. Bar Charts and Histograms
Histogram refers to a graphical representation, that displays data by way of bars to show the frequency of numerical data – uses quantitative data (numerical)
Bar graph is a pictorial representation of data that uses bars to compare different categories of data – use categorical data

15. Histogram – because each column represents a continuous quantitative variable
X axis is your independent variable and y axis is your dependent variable
Marks for test are dependent on hours spent studying – therefore marks are the
dependent variable and hours spent studying is the independent variable