Introduction To Statistics

    * Introduction* Statistics As Plural, As Data* Statistics As Singular, As A Subject* Meaning And Scope Retraced* Two Major Divisions Of Statistics : Descriptive Statistics, Inferential Statistics* Statistics And Risk Evaluation* More On Statistical Methods* Statistical Reasoning* Distrust In Statistics* Increasing Tentacles Of Statistics* (Sigma) Operation* Rules Of Sigma Operation* Try To Attempt* Solve And Check Up

2. Types Of Data : Bases Of Classification

    * Introduction* Factors Determining Types Of Data* Types Of Data Based On The Nature Of Variable(s) : Continuous Data, Discrete Data* Types Of Data Based On The Kind Of Characteristic(s) : Quantitative Data, Qualitative Data* Types Of Data Based On The Source(s) Of Compilation/Collection : Secondary Data, Primary Data* Try To Attempt

3. Data Collection : Issues And Methods

    * Introduction* Issues In Secondary Data Collection : External And Internal Sources Of Secondary Data, Primary And Secondary Sources Of Secondary Data, Cautions In Using Secondary Data, Evaluating Secondary Data* Issues In Primary Data Collection : Population Survey vs Sample Survey, Why Sample Surveys,  Accuracy And Errors* Sampling And Sampling Methods : Basic Sampling Concepts,  Sampling Methods* Techniques Of Data Collection :  Personal Interviews,  Telephone Interviews, Mailed Questionnaire* Preparing A Questionnaire* Pre-Testing And Editing A Questionnaire* Try To Attempt

4. Understanding Data : Rounding, Ratios, And Rates

    * Introduction* Errors In Data Restated* Errors Of Rounding : Need For Rounding Of Data, Rules Of Rounding Of Data* Ratios, Proportions, And Relatives : Types Of Ratios, Precautions In Using Ratios* Rates (rates of change)* Try To Attempt

5. Presentation Of Data : Tabular And Graphic

    * Introduction* Methods Of Presenting Data* Tabular Presentation : Types Of Tables, Components Of A Table* How To Frame Tables* Contingency Table(s)* Graphic Presentation* Types Of Graphs : Simple Bar Charts, Component Charts, Pie Charts* Try Yo Attempt* Draw And Check Up

6. Frequency Distribution : Construction And Graphic Presentation

    * Introduction* Raw Data* An Ordered Array* A Frequency Distribution* How To Construct A Frequency Distribution : Tally Method, Entry Form Method* Types Of Frequency Distributions* More On Frequency Distribution(s)* Concerns In Constructing A Frequency Distribution : Number Of Classes, Width Of The Class Interval(s), Establishing The Initial Class, Stated And Real Class Limits* Other Issues :  Unequal Class Intervals, Open-Ended Class Intervals* Graphic Presentation Of Frequency Distribution* Histogram : For Equal Class Intervals, For Unequal Class Intervals* Frequency Polygon* Comparing Frequency Distributions* Smoothen A Frequency Polygon* Frequency Distribution Models* A Cumulative Frequency Curve (or ogive).* Try To Attempt

7. Measures Of Central Tendency : Mean, Median, And Mode

    * Introduction* Central Tendency* Measures Of Central Tendency* Arithmetic Mean, And Its Computation : Properties Of Arithmetic Mean, The More Efficient Methods(s) Restated* Median, And Its Computation : Properties Of Median, Locating Median From An Ogive* Mode, And Its Computation : Properties Of Mode* How Are Mean, Median, And Mode Related* The Three Measures Compared* Introducing Other Measures : Geometric Mean, And Its Computation, Harmonic Mean, And Its Computation* Partition Values : Quartiles, Deciles, Percentiles* Review Problems* Try To Attempt* Solve And Check Up

8. Dispersion : And Its Measures

    * Introduction* Dispersion Defined* Measures Of Dispersion* The Range, And How To Obtain It* Quartile Deviation, And Its Computation* Mean Absolute Deviation, And Its Computation* Variance, And Its Computation : The Alternative Method, The Efficient Method, Properties Of Variance* Standard Deviation, And Its Computation*  Empirical Relationship Among Measures Of Dispersion* Relative Measures Of Dispersion : Coefficient Of Variation, Coefficient Of Quartile Deviation, Coefficient Of Mean Absolute Deviation* Measures Of Dispersion Compared* Moments : Moments About The Origin, Moments About The Mean* Review Problems* Try To Attempt* Solve And Check Up

9. Skewness And Kurtosis : And Measures

    * Introduction* Skewness, And Its Measures : Pearsonian Measure Of Skewness, Bowley's Measure Of Skewness, Moment Coefficient Of Skewness* Kurtosis, And Its Measures : Moment Coefficient Of Kurtosis, Percentile Coefficient Of Kurtosis* Review Problems* Try To Attempt* Solve And Check Up

10. Linear Regression And Correlation : The Two-Variable Case

      * Introduction* Regression And Correlation* Types Of Relationship* Linear Regression : The Scatter Diagram, Fitting A Straight Line, Methods Of Fitting A Straight Line, Determining The Constants, Obtaining The Best Fit* Predicting An Estimate And Its Preciseness* Measuring The Error Of Estimate(s) : The Alternative Method,  Interpretations of Sy.x* Regression Of X On Y* Regression And Causality* Measuring The Degree Of Relationship, The Correlation* Correlation Coefficient In Terms Of Regression Coefficients* Regression Coefficients In Terms of R, Sx, And Sy* Modifying The Two Regression Equations* Computation Of R From Cross-Classified Data* Correlation Of Ranks* Review Problems* Try To Attempt* Solve And Check Up

11. Index Numbers : For Prices And Quantities

      * Introduction* Index Number, As A Concept* Types Of Index Numbers*  Notations Used* Simple Index Numbers* Simple Aggregative Price (quantity) Indices :  Index Of Simple Aggregative  Prices (Quantities), Index Of Average Of Price (Quantity) Relatives* Weighted Aggregative Price (quantity) Indices : Those Using Base Period Quantities (Prices) As Weights, Those Using Given Period Quantities (Prices) As Weights, Relationship Between Laspeyre's And Paasche's Indices, More On The Two Indices* Other Aggregative Indices : Marshall-Edgeworth Index, Fisher's Ideal Index*  Tests Of Adequacy Of Index Numbers : The Time Reversal Test, The Factor Reversal Test* Shifting Base And Splicing : Shifting The Base, Splicing Two Index Number Series, Chain Base Index Numbers* Uses Of Index Numbers* Problems In Constructing Index Numbers* Review Problems* Try To Attempt* Solve And Check Up

12. Time Series Analysis : Components And Decomposition

      * Introduction* Meaning And Need* Time Series Graphs : Logarithmic Charts*  Types Of Time Series Variations* The Four Components Characterised : The Secular Trend, Cyclical Variations, Seasonal Variations, Random Variations* Approaches To Time Series Analysis : The Additive Approach, The Multiplicative Approach* Adjusting The Time Series* The Decomposition Process* Estimating Trend Variations : Methods Of Estimating Straight-Line Trend, Detrending A Time Series* Estimating Seasonal Variations : Methods Of Constructing Seasonal Index, Adjusting Time Series For Seasonal Variations, Seasonal Index And Future Estimation* Estimating Cyclical Variations* Review Problems* Try To Attempt* Solve And Check Up

13. Introducing Probability : Concepts, Definition, And Postulates

      * Introduction* Need And Relevance* Related Terms And Concepts : A Trial And An Experiment, Sample Points And Sample Space, A Generalisation, Random Sampling* Events : Types Of Events, Rules Of Event Operations* Methods Of Counting The Sample Points : The Fundamental Principle, Permutations, Set Partitioning, Combinations* Three Approaches To Define Probability* Basic Probability Postulates* Review Problems* Try To Attempt* Solve And Check Up

14. Basic Probability Rules : For Different Events

      * Introduction* The Additive Rules : Additive Rule For Mutually Exclusive Events, Additive Rule For Overlapping Events* The Complementation Rule For Complementary Events* The Conditional Probability Rules* Joint And Marginal Probabilities* The Multiplication Rules : Multiplication Rule For Dependent Events, Multiplication Rule For Independent Events* The Bayesian Probability Rrule : Bayesian Rule Generalised* Review Problems* Try To Attempt* Solve And Check Up

15. Discrete Probability Distributions : Uniform, Binomial, And Poisson

     * Introduction* A Discrete Random Variable And The Modified Sample Space* A Discrete Probability Distribution : Discrete Probability Distribution Charts, Expectation And Other Characteristics Of A Discrete Distribution* Some Discrete Probability Distributions* Uniform Distribution* Binomial Distribution : Characteristics Of A Binomial Experiment, A Binomial Trial, Parameters Of The Binomial Distribution,  Developing The Binomial Probability Rule, Binomial Expansion, Binomial Probability Tables, Characteristics Of A Binomial Distribution, Fitting A Binomial Distribution*  Poisson Distribution : Poisson Distribution Function, Cumulative Poisson Probability Table(s), Estimation Of µ, Fitting A Poisson Distribution, Characteristics Of The Poisson Distribution, Poisson Distribution As A Limiting Form Of The Binomial Distribution* Review Problems* Try To Attempt* Solve And Check Up

16. The Normal Distribution

      * Introduction* Continuous Probability Distribution Defined* Identifying The Shape Of A Continuous Distribution* Normal Probability Distribution* Normal Distribution Function And Its Parameters* Properties Of The Normal Curve* Need For Standardising The Normal Curve* Standard Normal Variable* Standard Normal Area Tables* Illustrations* Important Area Relationships* Normal Distribution As A Limiting Form Of The Binomial Distribution : For Symmetrical Binomial Distributions, For Skewed Binomial Distributions* Review Problems* Try To Attempt* Solve And Check Up

Appendices

Index

 

 

 

 

This text meets the elementary course needs of those new to learning statistics at the school or college level. Application-oriented methods including regression, correlation have been presented in simple terms.