Confidence Intervals R Code Part 1

The following code produces confidence intervals in R using the normal distribution and confidence intervals using the t-distribution.

The code reproduces the figure 1 presented in this post.

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Linear Regression in Julia 1.0

Julia presents various ways to carry out linear regressions. In this previous post, I explained how to run linear regression in Julia using the function linreg(). Unfortunately, linreg() is deprecated and no longer exists in Julia v1.0.

In this post I will present how to use the native function of Julia to run OLS on the following model

y = \alpha + \beta_{1} x_{1}

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What is the difference between using the t-distribution and the Normal distribution when constructing confidence intervals?

This blog post explains the difference between confidence intervals that use the t-distribution and confidence intervals that use the Normal distribution. Thereby, the post will not focus on the theoretical/mathematical differences of the two distributions, but rather compare the two types of confidence intervals using simulation studies. Furthermore, in case you are interested in replicating the presented results or simply play around with it yourself, I provide the R code to conduct the simulation exercises and to replicate the figures.

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How to Enable Gui Root Login in Debian 10

In this post I am going to explain how to enable GUI root access on Debian 10. It is very similar to enabling Gui Root Login in Debian 8 and to enabling Gui Root Login in Debian 9. At this point I should warn you that using the root account is dangerous as you can ruin your whole system.  Try to follow this guide exactly.

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Confidence Intervals in R

In this post, I will show how one can easily construct confidence intervals in R. Assume you have a vector of numbers and you want to construct a confidence interval around the mean of this vector. The subsequent R code shows one easy way to calculate the confidence interval around the mean of this vector. The following code loads a function that allows you to pass on the vector and returns the confidence intervals. Per default the function returns the 95% confidence interval. However, the parameter ‘conf_level’ allows you to specify the interval you want.

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“In God we trust; all others must bring data.” W. Edwards Deming

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