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introduction to statistics
introduction to statistics
This course introduces the basic statistical concepts in general applications. The topics include basic concepts of sampling methods, method of data collection, introductory methods in descriptive and inferential statistics. Specific topics include methods of describing data, correlation & regression analysis, time series analysis, index numbers and probability. Students will be exposed to statistical project which involve analyzing primary or secondary data in enhancing their understanding in solving real problems. Statistical Analysis using Excel or SPSS will be introduced.
1. Introduction to Statistics
1.1) Definition of statistics
1.2) Terms in statistics
1.3) Types of statistics
1.4) Sources of data
1.5) Types of variable
1.6) Scale of measurement
1.7) Sampling techniques
1.8) Data Collection Methods
2. Describing Data
2.1) Data organization and presentation
2.2) Measures of Central Tendency
2.3) Measures of Location
2.4) Measures of Dispersion
2.5) Measures of Skewness
Due to unforeseen circumstances, the next classes would be on digital platform (classroom.google.com).
Please get the class code from your class rep.
Thank you.
1) Watch the video.
2) submit the assignments.
Topics covered here are
1) Organizing data
frequency distribution (grouped and ungrouped data)
relative frequency distributions
cumulative frequency distribution
2) graphing quantitative data
histogram
frequency polygon
cumulative frequency polygon (ogive)
Stem and leaf
3. Correlation and Regression
3.1) Correlation (Pearson's Product Moment Correlation)
3.2) Simple linear regression
4. Index Number
4.1) Types of index numbers
4.2) Calculate and explain unweighted index numbers
4.3) Calculate and explain weighted index number
5. Time Series
5.1) Component of time series
5.2) Multiplicative time series model
5.3) Trend Analysis (Moving Average Method)
5.4) Seasonal Variations
5.5) Forecasting
6. Introduction to Probability
6.1) Set theory
6.2) Addition rules
6.3) Multiplication rules and conditional probability
6.4) Counting rules (Permutations and Combinations)
6.5) Tree Diagram
6.6) Bayes' Theorem
Using contigency table to solve probability problem.
Example of Research STA104.pdfPage updated
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