Statistics Masterclass: Stats Using SPSS, Excel, R & Python

Explore ordinal scales as ordinal variables with rank ordering, illustrated by education level, tall/short/average height, and socioeconomic status.

Examine the debate whether Likert scales are ordinal or interval, including constant spacing assumptions. Conclude that current consensus treats Likert scales as ordinal in social science.

Explore how to build a frequency distribution from a market survey of favorite eating options, determine total respondents, and count each option using manual tally or Excel.

Create numeric and string vectors in R using the assignment operator and c, assign values to score or marks, and build a performers vector with quotes to verify with mean.

Define geometric mean as the nth root of the product of sample values and illustrate with a dataset of ten students' marks, using log transformation and anti log in Excel.

Learn to calculate geometric mean using three methods: nth root, log-based methods, and the geo mean function in Excel, with a practical example and cross-method validation.

Explore the properties of the harmonic mean and its use for rates, speed, or ratios. Avoid it with zeros, no change, or large and small disparities.

Learn to calculate the mean for grouped data using midpoints and frequencies, applying the formula sum f x over sum f to analyze office absenteeism and guide HR decisions.

Learn to calculate quartiles for discreet data in an even ungrouped series, using Q1 = (n+1)/4 and Q3 = (3n+1)/4, with Excel sorting and interpolation.

Calculate quartiles for class interval data using Q1 and Q3 with n, cf, f, and L1/L2, illustrated by real estate price data to guide pricing decisions.

Learn to calculate quartiles in SPSS through analyze, frequencies, move the variable to the box, select quartiles, and compare with Excel; first quartile 25.25 and third quartile 74.

Compute the seventh decile for continuous data in a class interval using the decile formula with L1, L2, f, cf, n, and k.

Compare percentile calculations across inclusion and exclusion methods using SPSS and Excel, estimating 70th, 85th, and 90th percentiles, noting slight method-based differences.

Compute the range for continuous data or the coefficient of range by subtracting the lower limit from the upper limit in class intervals, using real estate price data.

Master mean deviation as a dispersion measure and learn to calculate it for range and quartile deviation alongside individual, discrete with frequency, and continuous class interval data.

Learn to calculate the sample standard deviation for ungrouped data in SPSS by importing data from Excel, using descriptive statistics, and validating results with mean, min, max, and variance.

Learn how to calculate population standard deviation and compare it with SPSS's sample standard deviation, and note that SPSS provides only sample SD, requiring manual population SD calculation in Excel.

Explore symmetric and asymmetric distributions by examining how data align around the mean, median, and mode, with examples from sales and IQ scores.

Describe skewness as distortion from the normal distribution, and distinguish positive skewness (left-heavy data with a right tail) from negative skewness (right-heavy data with a left tail).

Bowley's coefficient of skewness uses quartiles to assess skewness, comparing median distances to Q1 and Q3 with the difference between Q3 and Q1, signaling positive, negative, or zero skewness.

Get familiar with the Jupyter notebook interface by creating and running Python cells, and by copying, pasting, and deleting them, and by writing code.