Download For details, please refer to the class notes distributed Lecture 1

For details, please refer to the class notes distributed
Lecture 1. Introduction
Statistics-population-parameter-sample-statistic
Data classification:
Qualitative-quantitative
Discrete-continuous
Level of measurement: nominal-ordinal-interval-ratio
Lecture 2.Frequency distributions
Frequency distribution: class frequency, class midpoint, class interval
Relative frequency
Cumulative frequency
Tabular form: how to develop a frequency distribution table-five-step procedure
Graphical form for quantitative:
Histogram: frequency, relative, and cumulative
Polygon: frequency, relative, and cumulative
Graphical form for qualitative
Bar chart:
Pie chart
Represent medium size data without loss of information
Stem-and-leaf
Lecture 3. Measure of Central Tendency
Mean:
Arithmetic mean and weighted mean
Raw data
Grouped data
Geometric mean
Median
Raw data
Grouped data
Mode
Raw data
Grouped data
Lecture 4. Measure of Dispersion (no calculation on skewness, Kurtosis, correlation)
Range
Raw data
Grouped data
Mean absolute deviation
Population
Sample
Variance and standard deviation
Raw data
 fx

2
Grouped data:  
Population:  
Sample:  
 f ( x  x)
n 1
 (x  )
2

 fx
2
n 1
n
2
n
 ( x  x)
2
n 1
Conceptual formula
Computational formula
Cehbyshev’s Theorem
Empirical rule (68, 95, 99.7)
Compare more than one data set with different units or one data set with
widespread mean:
Coefficient of variation
Population: CV 
Sample: CV 


x

