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Helsinki Social Statistics

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12 Horas66 Exercicios
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Descrição do Curso

This DataCamp course has been developed by Tuomo Nieminen and Emma Kämäräinen, under the supervision of adj. prof. Kimmo Vehkalahti. This course works as the Data Science module for the Social Statistics MOOC at the University of Helsinki, Finland.
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  1. 1

    R and statistics

    Grátis

    Basics of R, the amazing statistical programming language. Do not be afraid of the art of programming!

    Reproduzir Capítulo Agora
    What is R?
    100 xp
    Basic tools
    100 xp
    Arithmetics
    100 xp
    Objects
    100 xp
    Functions
    100 xp
    Good arguments
    100 xp
    students2014
    50 xp
  2. 2

    Data types and variable types

    Grátis

    Quick overview to R data and variable types. What are the objects? You are the subject.

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    Data frames
    100 xp
    Data types (1)
    100 xp
    Data types (2)
    100 xp
    Vectors
    100 xp
    Data types and measurement scales
    50 xp
  3. 3

    Looking at the data

    Grátis

    Data are everywhere and everything. That's why Statistics is also called Data Science. R offers great tools for looking at the data, behind the numbers.

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    Getting intimate with the data
    100 xp
    Summary() statistics
    100 xp
    Bar plots of qualitative variables
    100 xp
    Bar plots of continuous variables
    100 xp
    Histograms
    100 xp
    Box plots
    100 xp
  4. 4

    Exploring variation and dependence

    Grátis

    Variation and dependence are at the heart of Statistics. In fact, without variation the discipline would cease to exist. Correlation is not causation, but why?

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    Be aware of varying variables
    100 xp
    Help() !
    100 xp
    Standard deviation
    100 xp
    Clustering
    100 xp
    Guess the correlation
    100 xp
  5. 5

    Working across the data

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    Cross-tabulations let you explore dependencies hidden deep within discrete variables.

    Reproduzir Capítulo Agora
    Combining variables
    100 xp
    Tables
    100 xp
    Metadata of students2014
    50 xp
    Cross tabulations
    100 xp
    Let's (bar)plot that table
    100 xp
    And then little more plotting
    100 xp
  6. 6

    Subsets and conditions

    Grátis

    Let's begin to seek the best conditions for coping with uncertainty.

    Reproduzir Capítulo Agora
    Welcome to part 2!
    100 xp
    Explore your data
    50 xp
    Selecting a subset()
    100 xp
    Logical comparison
    100 xp
    Logical operators
    100 xp
    Classical probability
    100 xp
    Conditional probability
    100 xp
  7. 7

    Probability distributions

    Grátis

    Most things in this world are more or less random, and not evenly distributed.

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    Random variables and probability distributions
    100 xp
    Binomial distribution
    100 xp
    Normal distribution (1)
    100 xp
    Normal distribution (2)
    100 xp
    Uniform distribution
    50 xp
    Quantiles
    100 xp
    Two-way quantiles
    100 xp
    Standardization
    100 xp
  8. 8

    Estimation

    Grátis

    Get your brackets ready for diving in the world of statistical inference!

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    Exploring estimation with R
    100 xp
    Indices and brackets
    100 xp
    Easy vectors
    100 xp
    Looping
    100 xp
    Point estimation
    100 xp
    Interval estimation
    100 xp
    The sampling distribution
    100 xp
    The central limit theorem
    100 xp
  9. 9

    Hypothesis testing

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    We all might be statistically different, but maybe we are part of the 68%.

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    Statistical hypothesis testing
    50 xp
    Test statistics
    100 xp
    Peculiar p-values
    100 xp
    Alternative hypothesis: which way to go?!
    50 xp
    Meet the tests! (1)
    100 xp
    Meet the tests! (2)
    100 xp
    Create your own functions
    100 xp
  10. 10

    Regression

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    Now, pick roles for the variables and start modeling. I predict you are good!

    Reproduzir Capítulo Agora
    Packages in R
    100 xp
    Exploring the relationship of two variables
    100 xp
    What is a linear model?
    100 xp
    Fitting a linear model
    100 xp
    Interpreting a fitted model
    50 xp
    Checking the validity of model assumptions
    50 xp
    Making predictions based on the model
    100 xp
Para Empresas

GroupTreinar 2 ou mais pessoas?

Obtenha acesso à biblioteca completa do DataCamp, com relatórios, atribuições, projetos e muito mais centralizados

Nas seguintes faixas

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Kimmo Vehkalahti HeadshotKimmo Vehkalahti

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