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Curso gratuito

Basic Statistics

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8 horas153 ejercicios
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Descripción del curso

This course complements course material from the University of Amsterdam's Basic Statistics at Coursera (www.coursera.org/learn/basic-statistics). The Basic Statistics course is roughly based on the syllabus used by the department of Child Development and Educational Sciences at the University of Amsterdam (produced by A. van Maanen, A.A.J. van Peet, N. Borgers, E. Gebhardt, N. Lagerweij, R. Stoel, G. van de Wittenboer, F.J. Oort, P.J. Hoffenaar, and B.J.H. Zijlstra.)
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  1. 1

    The Basics of R

    Gratuito

    This lab is about teaching enough R to start using it for statistical analyses.

    Reproducir Capítulo Ahora
    How it works
    100 xp
    Little arithmetics with R
    100 xp
    Documenting your code
    100 xp
    Variable assignment I
    100 xp
    Variable assignment II
    100 xp
    Back to Apples and Oranges
    100 xp
    Discover Basic Data Types
    100 xp
    What's that data type?
    50 xp
    Coercion: Taming your data
    100 xp
    Create a vector I
    100 xp
    Vectors II
    100 xp
    Selection by comparison I
    100 xp
    Selection by comparison II
    100 xp
    Matrices
    100 xp
    Factors
    100 xp
    Dataframes: What's a data frame?
    100 xp
    Inspecting dataframes
    100 xp
    Constructing a dataframe yourself
    100 xp
    Indexing and selecting columns from a dataframe
    100 xp
    Lists
    100 xp
    Selecting elements from a list
    100 xp
  2. 2

    Introduction to R continued

    Gratuito

    This lab continues with an introduction to R

    Reproducir Capítulo Ahora
    Making a start with functions: Getting help
    100 xp
    Functions continued
    100 xp
    Functions continued II
    100 xp
    Making your own functions
    100 xp
    Getting your data into R
    100 xp
    Reading in your own data
    100 xp
    Working directories in R
    100 xp
    Changing working directories in R
    100 xp
    Checking files in your working directory
    100 xp
    Importing R packages
    100 xp
  3. 3

    Exploring Data

    Gratuito

    Getting to grips with your data

    Reproducir Capítulo Ahora
    Checking the dimensions of your data
    100 xp
    Data Structure
    50 xp
    Levels
    100 xp
    Recoding Variables
    100 xp
    Examining Frequencies
    100 xp
    Cumulative Frequency
    100 xp
    Making a Bar Graph
    100 xp
    Labelling A Bar Graph
    100 xp
    Interpreting A Bar Graph
    50 xp
    Histograms
    100 xp
    Formatting Your Histogram
    100 xp
    Bar Graph vs. Histogram
    50 xp
    Distributions
    50 xp
    Mean and Median
    100 xp
    Mode
    100 xp
    Range
    100 xp
    Quartiles
    100 xp
    IQR and boxplot
    100 xp
    IQR outliers
    100 xp
    Standard Deviation
    100 xp
    Mean, median and mode.
    50 xp
    Calculating Z-scores
    100 xp
    Distributions And Z-scores
    50 xp
    Z-score Outliers
    50 xp
  4. 4

    Correlation and Regression

    Gratuito

    Looking at the relationships between two variables.

    Reproducir Capítulo Ahora
    Scatterplots
    100 xp
    Making a Contingency Table
    100 xp
    Calculating Percentage From Your Contingency Table
    100 xp
    Interpreting Your Scatterplot
    50 xp
    Pearson's R I
    50 xp
    Pearson's R II
    50 xp
    Pearson's R III
    50 xp
    Pearson's R IV
    50 xp
    Calculating Correlation Using R
    100 xp
    Finding The Line
    100 xp
    Interpreting The Line
    100 xp
    The Regression Equation
    100 xp
    Describing The Line
    50 xp
    Finding The Regression Coefficients in R
    100 xp
    Using lm() To Add A Regression Line To Your Plot
    100 xp
    Adding A Line
    100 xp
    R Squared I
    100 xp
    R Squared II
    50 xp
    Correlation and Causation
    50 xp
    Putting It Together: Regression
    100 xp
    Putting It Together: Contingency Tables
    100 xp
  5. 5

    Probability

    Gratuito

    Understanding the basics of probability

    Reproducir Capítulo Ahora
    Randomness I
    50 xp
    Randomness II
    50 xp
    Probability I
    100 xp
    Probability II
    50 xp
    Sample Space I
    100 xp
    Sample Space II
    100 xp
    Probability Tree I
    100 xp
    Probability Tree II
    100 xp
    Probability Terms I
    100 xp
    Probability Terms II
    100 xp
    Probability Terms III
    100 xp
    Practise With Sets I
    100 xp
    Practise With Sets II
    100 xp
    Practise With Sets III
    100 xp
    Unions
    100 xp
    Joint and Marginal Probabilities
    100 xp
    Conditional Probability I
    100 xp
    Independence
    100 xp
    Conditional Probability II
    100 xp
    Bayesian Probability I
    50 xp
    Bayesian Probability II
    100 xp
  6. 6

    Probability distributions

    Gratuito

    This lab treats probability distributions with an emphasis on the normal and binomial distributions.

    Reproducir Capítulo Ahora
    Probability mass and density functions
    100 xp
    Probability mass and density functions (2)
    100 xp
    The cumulative probability distribution
    100 xp
    Summary statistics: The mean
    100 xp
    Summary statistics: Variance and the standard deviation
    100 xp
    The normal distribution
    50 xp
    The normal distribution and cumulative probability
    100 xp
    The normal distribution and quantiles
    100 xp
    The normal distribution and Z scores
    100 xp
    The binomial distribution
    100 xp
    Calculating probabilities of binomial distributions in R
    100 xp
    Quantiles and the binomial distribution
    100 xp
  7. 7

    Sampling distributions

    Gratuito

    This lab explores population and sampling distributions

    Reproducir Capítulo Ahora
    Sampling from the population
    100 xp
    Using a for loop
    100 xp
    Mean of the sampling distribution
    100 xp
    Standard deviation of the sampling distribution
    100 xp
    Standard deviation of the sampling distribution (2)
    50 xp
    The central limit theorem
    100 xp
    Zscores
    100 xp
    Calculating areas with subjects
    100 xp
    Interpreting areas under the curve
    50 xp
    Calculating areas with sample means
    100 xp
    Calculating areas with sample means (2)
    50 xp
    Sampling distributions and proportions
    100 xp
    Sampling distributions and proportions (2)
    100 xp
  8. 8

    Confidence Intervals

    Gratuito

    Calculating the interval where a value falls

    Reproducir Capítulo Ahora
    Sampling
    50 xp
    Point Estimate vs. Interval Estimate
    50 xp
    Confidence Interval With Known SD I
    100 xp
    Confidence Interval With Known SD II
    100 xp
    Calculating a Confidence Interval Without The Population Standard Deviation
    100 xp
    Assumptions For Calculating A Confidence Interval
    50 xp
    Calculating A Confidence Interval for a Proportion I
    100 xp
    Calculating A Confidence Interval for a Proportion II
    100 xp
    Calculating A Confidence Interval for a Proportion III
    100 xp
    Calculating A Confidence Interval for a Proportion IV
    50 xp
    Other Types Of Confidence Intervals I
    100 xp
    Other Types Of Confidence Intervals II
    100 xp
    Other Types Of Confidence Intervals III
    50 xp
    Other Types Of Confidence Intervals IV
    50 xp
    Sample Size I
    50 xp
    Sample Size II
    100 xp
    Sample Size III
    100 xp
    Sample Size IV
    100 xp
  9. 9

    Hypothesis testing

    Gratuito

    This lab treats the concept of hypothesis testing for both binomial and normally distributed variables

    Reproducir Capítulo Ahora
    Significance testing recap
    50 xp
    Significance testing: one-sided versus two-sided
    100 xp
    Significance testing: one-sided versus two-sided (2)
    100 xp
    Significance testing: one-sided versus two-sided (3)
    100 xp
    Significance testing: one-sided versus two-sided (4)
    100 xp
    Hypothesis testing and the binomial distribution
    50 xp
    Hypothesis testing and the binomial distribution (2)
    100 xp
    Hypothesis testing and the binomial distribution (3)
    100 xp
    The t distribution
    100 xp
    The t distribution (2)
    100 xp
    Confidence interval and significance testing
    100 xp
    Confidence interval and significance testing (2)
    50 xp
    Confidence interval and significance testing (3)
    50 xp
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