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fix int/float + ength

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behinger (s-ccs 001) 2023-10-09 12:55:18 +00:00
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commit 96efdd56d1
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material/1_mon/firststeps/tasks.qmd
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@ -14,9 +14,9 @@ You can mark some code and execute it using `ctrl` + `enter` - you can also gene
3. implement a second function called `rse_mean`, which calculates the mean of the provided vector. Make sure to use the `rse_sum` function! Test it using `rse_mean(-15:17) == 1`
4. Next implement a standard deviation function `rse_std`: $\sqrt{\frac{\sum((x-mean(x))^2)}{n-1}}$, this time you should use elementwise/broadcasting operators. Test it with `rse_std(1:3) == 1`
4. Next implement a standard deviation function `rse_std`: $\sqrt{\frac{\sum((x-mean(x))^2)}{n-1}}$, this time you should use elementwise/broadcasting operators. Test it with `rse_std(1:3) == 1.`
5. Finally, we will implement `rse_tstat`, returning the t-value with `length(x)-1` DF, that the provided Array actually has a mean of 0. The formula is $\frac{mean(x)}{std(x) / (sqrt(x))}$ Test it with `rse_tstat(2:3) == 5`. Add the keyword argument `σ` that allows the user to optionally provide a pre-calculated standard deviation.
5. Finally, we will implement `rse_tstat`, returning the t-value with `length(x)-1` DF, that the provided Array actually has a mean of 0. The formula is $\frac{mean(x)}{std(x) / (sqrt(length(x)))}$ Test it with `rse_tstat(2:3) == 5.`. Add the keyword argument `σ` that allows the user to optionally provide a pre-calculated standard deviation.
Well done! You now have all functions defined with which we will continue our journey.