Statistics Tutorial
Selected Reading
- Statistics - Discussion
- Z table
- Weak Law of Large Numbers
- Venn Diagram
- Variance
- Type I & II Error
- Trimmed Mean
- Transformations
- Ti 83 Exponential Regression
- T-Distribution Table
- Sum of Square
- Student T Test
- Stratified sampling
- Stem and Leaf Plot
- Statistics Notation
- Statistics Formulas
- Statistical Significance
- Standard normal table
- Standard Error ( SE )
- Standard Deviation
- Skewness
- Simple random sampling
- Signal to Noise Ratio
- Shannon Wiener Diversity Index
- Scatterplots
- Sampling methods
- Sample planning
- Root Mean Square
- Residual sum of squares
- Residual analysis
- Required Sample Size
- Reliability Coefficient
- Relative Standard Deviation
- Regression Intercept Confidence Interval
- Rayleigh Distribution
- Range Rule of Thumb
- Quartile Deviation
- Qualitative Data Vs Quantitative Data
- Quadratic Regression Equation
- Process Sigma
- Process Capability (Cp) & Process Performance (Pp)
- Probability Density Function
- Probability Bayes Theorem
- Probability Multiplecative Theorem
- Probability Additive Theorem
- Probability
- Power Calculator
- Pooled Variance (r)
- Poisson Distribution
- Pie Chart
- Permutation with Replacement
- Permutation
- Outlier Function
- One Proportion Z Test
- Odd and Even Permutation
- Normal Distribution
- Negative Binomial Distribution
- Multinomial Distribution
- Means Difference
- Mean Deviation
- Mcnemar Test
- Logistic Regression
- Log Gamma Distribution
- Linear regression
- Laplace Distribution
- Kurtosis
- Kolmogorov Smirnov Test
- Inverse Gamma Distribution
- Interval Estimation
- Individual Series Arithmetic Mode
- Individual Series Arithmetic Median
- Individual Series Arithmetic Mean
- Hypothesis testing
- Hypergeometric Distribution
- Histograms
- Harmonic Resonance Frequency
- Harmonic Number
- Harmonic Mean
- Gumbel Distribution
- Grand Mean
- Goodness of Fit
- Geometric Probability Distribution
- Geometric Mean
- Gamma Distribution
- Frequency Distribution
- Factorial
- F Test Table
- F distribution
- Exponential distribution
- Dot Plot
- Discrete Series Arithmetic Mode
- Discrete Series Arithmetic Median
- Discrete Series Arithmetic Mean
- Deciles Statistics
- Data Patterns
- Data collection - Case Study Method
- Data collection - Observation
- Data collection - Questionaire Designing
- Data collection
- Cumulative Poisson Distribution
- Cumulative plots
- Correlation Co-efficient
- Co-efficient of Variation
- Cumulative Frequency
- Continuous Series Arithmetic Mode
- Continuous Series Arithmetic Median
- Continuous Series Arithmetic Mean
- Continuous Uniform Distribution
- Comparing plots
- Combination with replacement
- Combination
- Cluster sampling
- Circular Permutation
- Chi Squared table
- Chi-squared Distribution
- Central limit theorem
- Boxplots
- Black-Scholes model
- Binomial Distribution
- Beta Distribution
- Best Point Estimation
- Bar Graph
- Arithmetic Range
- Arithmetic Mode
- Arithmetic Median
- Arithmetic Mean
- Analysis of Variance
- Adjusted R-Squared
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Scatterplots
Statistics - Scatterplots
A scatterplot is a graphical way to display the relationship between two quantitative sample variables. It consists of an X axis, a Y axis and a series of dots where each dot represents one observation from a data set. The position of the dot refers to its X and Y values.
Patterns of Data in Scatterplots
Scatterplots are used to analyze patterns which generally varies on the basis of pnearity, slope, and strength.
Linearity - data pattern is either pnear/straight or nonpnear/curved.
Slope - direction of change in variable Y with respect to increase in value of variable X. If Y increases with increase in X, slope is positive otherwise slope is negative.
Strength - Degree of spreadness of scatter in the plot. If dots are widely dispersed, the relationship is consider weak. If dot are densed around a pne then the relationship is said to be strong.
