Quick and Easy Basics of Core concepts of Statistics with Examples
This Statistics preparation material will cover the important concepts of Statistics syllabus. It contains chapters discussing all the basic concepts of Statistics with suitable examples.
Audience
This tutorial will give you great understanding on concepts present in Statistics syllabus and after completing this preparation material you will be at intermediate level of experties from where you can take yourself at higher level of expertise.
Prerequisites
Before proceeding with this tutorial you should have a basic understanding of Mathematics.
Concepts Covered
Adjusted R-Squared
Analysis of Variance
Arithmetic Mean
Arithmetic Median
Arithmetic Mode
Arithmetic Range
Bar Graph
Best Point Estimation
Beta Distribution
Binomial Distribution
Black-Scholes model
Boxplots
Central limit theorem
Chebyshev's Theorem
Chi-squared Distribution
Chi Squared table
Circular Permutation
Cluster sampling
Cohen's kappa coefficient
Combination
Combination with replacement
Comparing plots
Continuous Uniform Distribution
Cumulative Frequency
Co-efficient of Variation
Correlation Co-efficient
Cumulative plots
Cumulative Poisson Distribution
Data collection
Data collection - Questionaire Designing
Data collection - Observation
Data collection - Case Study Method
Data Patterns
Deciles Statistics
Dot Plot
Exponential distribution
F distribution
F Test Table
Factorial
Frequency Distribution
Gamma Distribution
Geometric Mean
Geometric Probability Distribution
Goodness of Fit
Grand Mean
Gumbel Distribution
Harmonic Mean
Harmonic Number
Harmonic Resonance Frequency
Histograms
Hypergeometric Distribution
Hypothesis testing
Interval Estimation
Inverse Gamma Distribution
Kolmogorov Smirnov Test
Kurtosis
Laplace Distribution
Linear regression
Log Gamma Distribution
Logistic Regression
Mcnemar Test
Mean Deviation
Means Difference
Multinomial Distribution
Negative Binomial Distribution
Normal Distribution
Odd and Even Permutation
One Proportion Z Test
Outlier Function
Permutation
Permutation with Replacement
Pie Chart
Poisson Distribution
Pooled Variance (r)
Power Calculator
Probability
Probability Additive Theorem
Probability Multiplecative Theorem
Probability Bayes Theorem
Probability Density Function
Process Capability (Cp) & Process Performance (Pp)
Process Sigma
Quadratic Regression Equation
Qualitative Data Vs Quantitative Data
Quartile Deviation
Range Rule of Thumb
Rayleigh Distribution
Regression Intercept Confidence Interval
Relative Standard Deviation
Reliability Coefficient
Required Sample Size
Residual analysis
Residual sum of squares
Root Mean Square
Sample planning
Sampling methods
Scatterplots
Shannon Wiener Diversity Index
Signal to Noise Ratio
Simple random sampling
Skewness
Standard Deviation
Standard Error ( SE )
Standard normal table
Statistical Significance
Statistics Formulas
Statistics Notation
Stem and Leaf Plot
Stratified sampling
Student T Test
Sum of Square
T-Distribution Table
Ti 83 Exponential Regression
Transformations
Trimmed Mean
Type I & II Error
Variance
Venn Diagram
Weak Law of Large Numbers
Z table
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