What you Will study ?
- manipulate information in R (filter and type information units, recode and compute variables)
- compute statistical indicators (imply, median, mode and many others.)
- decide skewness and kurtosis
- get statistical indicators by subgroups of the inhabitants
- construct frequency tables
- construct cross-tables
- create histograms and cumulative frequency charts
- construct column charts, imply plot charts and scatterplot charts
- construct boxplot diagrams
- verify the normality assumption for a knowledge sequence
- detect the outliers in a knowledge sequence
- carry out univariate analyses (one-sample t take a look at, binomial take a look at, chi-square take a look at for goodness-of-fit)
If you wish to learn to carry out the essential statistical analyses within the R program, you could have come to the correct place.
Now you don’t need to scour the online endlessly so as to discover how one can compute the statistical indicators in R, how one can construct a cross-table, how one can construct a scatterplot chart or how one can compute a easy statistical take a look at just like the one-sample t take a look at. The whole lot is right here, on this course, defined visually, step-by-step.
So, what is going to you study on this course?
Initially, you’ll learn to manipulate information in R, to arrange it for the evaluation: how one can filter your information body, how one can recode variables and compute new variables.
Afterwards, we’ll take care about computing the primary statistical figures in R: imply, median, customary deviation, skewness, kurtosis and many others., each in the entire inhabitants and in subgroups of the inhabitants.
Then you’ll learn to visualize information utilizing tables and charts. So we’ll construct tables and cross-tables, in addition to histograms, cumulative frequency charts, column and imply plot charts, scatterplot charts and boxplot charts.
Since assumption checking is an important a part of any statistical evaluation, we couldn’t elude this matter. So we’ll learn to verify for normality and for the presence of outliers.
Lastly, we’ll carry out some fundamental, one-sample statistical assessments and interpret the outcomes. I’m speaking concerning the one-sample t take a look at, the binomial take a look at and the chi-square take a look at for goodness-of-fit.
So after graduating this course, you’ll know how one can carry out the important statistical procedures within the R program. So… enroll at present!
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- R and R studio
- data of fundamental statistics
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