This App can solve ANY AP Stats problem, read below:

• Show Step by Step solutions for most Statistics and Probability topics.
• Step by Step Confidence Intervals for mean, proportion, 2 means, 2 proportions, variance, slope, etc.
• Compute Sample Sizes for Confidence Intervals.
• Step by Step Tests of Significance (Z-Tests, T-Tests, ChiSquare Goodness of Fit and Independence tests, 2-sample T tests, 2 proportion Z tests, for Variance, etc)
• Step by Step F Test for 2 variances
• Step by Step Regression.
• Read about how Confidence Intervals behave.
• Read about Significant Tests: Type 1 Error, Type 2 Error, Power of a Test.
• Much easier handling than other Statistics packages: Choose to enter Data or Statistic values. Select Significant/Confidence Levels easily.
• Distributions: compute probabilities, etc.
• Includes Binomial, Geometric, Normal, Student-t, Uniform, Exponential, Poisson, Multinomial, Hypergeometric, F-, Chi-Square and more Distributions.
• Probability Checker for independent events, disjoint events. Also solves P(A or B)=P(A)+P(B)-P(A and B) for the unknown.
• Regressions: Linear , Quadratic, Cubic, Quartic, Sinusoidal, Logarithmic, Exponential, Power, MedMed
• Step by Step Derive the Coefficients for a Linear Regression Line, the Coefficient of Determination and the Correlation Coefficient.
• Also: Z-score Solver, Random Number Generator, etc
• 1 or 2 variable stats on mean, mode, median, standard deviation, variance, range
• Random Variables: Compute Variance, Expected Value and Standard Deviation.
• Additional Modules x`on: Probability, Combinatorics, Percentages, Ratios, Proportions, Exponential and Logarithmic Functions, Exponential Function Solver, Equation Solver

FUNCTIONALITY & MENU ITEMS OF APP :

• n1*n2*n3*.. = Multiplication Principle
• n! = Number of Rearrangements
• nPr = Number of ways to rearrange r given n
• nCr = Number of ways to pick r given n
• n^r = # ways to rearrange n items repeated r times
• (n+r-1)!/((n-1)!*r!) = Select r given n w. repetition
• Binomial Coefficients & Pascal Triangle
• Draw Random Number(s) over interval (with or without repeats)
• Draw Sample from Normal Distribution
• Draw Sample from Binomial Distribution
• Read: Introduction & Examples
• Read: Rules & Properties
• Odds <-> Probability
• Conditional Probability
• Expected Value: Find μ and s
• Read: Cards
• Read: Dice
• Read: Marbles
• Read: Coins
• P(A or B)=P(A)+P(B)-P(A and B)
• Check if A and B are dependent or disjoint
• P(A or B or C)
• Find Average
• Find Geometric Mean and Harmonic Mean
• Find Weighted Average
• Find Std Deviation
• Find Quartiles & 5-Number Summary
• Find Percentiles
• Z-score Solver
• Central Limit Theorem
• Survey Sampling
• Find Regression Line y=mx+b
• Find Regression Line y=mx+b given Mean, Standard Deviation, Correlation Coefficient r
• Find Predicted Value given y=mx+b
• Find Regression Line y=mx+b Step by Step
• Find Regression Line y=a+bx
• Read: All about Linear Regression
• Read: Correlation is not Causation!
• Find Median-Median Line y=mx+b
• Find Quadratic Regression y=ax^2+bx+c
• Find Cubic Regression y=ax^3+bx^2+cx+d
• Quartic Regression y=ax^4+bx^3+cx^2+dx+e
• Find Power Regression y=a*b^x
• Find Exponential Regression y=a*x^b
• Find Logarithmic Regression y=a+b*ln(x)
• Find Sinusoidal Regression y=a*sin(bx+c)+d
• Logistic Regression y=c*e^(bx)/(e^(bx)+a)
• Multiple Linear Regression y=b0+b1x+b2x
• Binomial Distribution Table
• Cumulative Binomial Distribution
• Inverse Binomial Distribution Solver: Find #successes given cumulative probability, success probability and #trials.
• Inverse Binomial Distribution Solver: Find #trials given cumulative probability, success probability and #successes.
• Negative Binomial Distribution
• Normal Distribution
• Bernoulli Trial Distribution
• Uniform Discrete Distribution
• Inverse Normal Solver
• READ: About Normal Distributions
• Exponential Distribution Table
• Geometric Distribution Table
• Uniform Distribution
• Cumulative Geometric Distribution
• Poisson Distribution Table
• Cumulative Poisson Distribution
• Student T-Distribution Table
• Cumulative T-Distribution
• Inverse T Solver
• Chi^2-Distribution Table
• Cumulative Chi^2-Distribution
• Inverse Chi^2-Solver
• F-Distribution Table
• Cumulative F-Distribution
• Inverse F-Solver
• Enter & Analyze your own Discrete Distribution
• READ: Properties of Continuous Distribution
• READ: Properties of Discrete Distribution
• Maximum Likelihood Parameter Estimation
• Error Function
• Complementary Error Function
• Read: Confidence Intervals & their Behavior
• CI for Mean μ with known Standard Deviation
• CI for Mean: Sample Size given Margin of Error
• CI for 2 Means with known Standard Deviations
• CI for Mean μ with unknown Standard Deviation
• CI for 2 Means with unknown Standard Deviations
• Pooled Standard Deviation and Variance
• CI for Proportion p using Normal Distr.
• CI for Proportion p using exact Bliss method
• CI for p: Sample Size given Margin of Error
• CI for 2 Proportions
• CI for Variance s^2 of Population
• CI for Variance s^2 of Sample
• Linear Regression Slope b Confidence Interval
• Multiple Linear Regression Confidence Interval
• Read: About Tests of Significance
• Z-Test for Mean Ho:μ=μo
• Z-Test for Means Ho:μ1=μ2
• Pooled Standard Deviation and Variance
• Z-Test for Proportion Ho:p=po
• Z-Test for Proportions Ho:p1=p2
• T-Test for Mean Ho:μ=μ_o
• T-Test for Means Ho:μ1=μ2
• F-Test for Ho:s1=s2
• Slope of Linear Regression Significance Test
• Multiple Linear Regression Significance Test
• ChiSquared-Test: Goodness of Fit
• ChiSquared-Test of Independence
• ChiSquared-Test of Heterogeneity
• Kruskal Wallis
• Sign Tests
• Wilcoxon Signed Rank Tests
• Wilcoxon Rank Sum Tests
• U-Test Mann Whitney
• Friedman Test
• Stochastic and Regular Stochastic Matrix
• Probability Vector
• Terminal State & Fixed Probability Vector
• Find A^n
• nth State of a Markov Chain: po*A^n
• Moving Average
• Exponential Smoothing
• Decision Analysis: MiniMax, Maxi-Max, Maxi-Min, Expected Value Strategies
• Find Moment Generating Function of Exponential Function
• Find Mean and Variance of a Moment Generating Function

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