Update multiple pages (some more minor changes) (#15)

* Update check-alpha.qmd (format R output as block quote instead of line block)

* Update check-power.qmd (formatting of numbered exercise list)

* Update repeat.qmd (rm bullet point breaking up a sentence)

* Update real-life-example.qmd (rm empty space)

* Update README.md and index.qmd (capitalize "Dry" in tutorial overview)

* Update random-numbers-generators.qmd (reword task to use actual file names instead of referring to non-existent file)

* Update dry-rule.qmd (rm empty space)

README.md

@@ -31,7 +31,7 @@ It is necessary that you work through the sections of the tutorial in order. Ple
 * [Setting the seed](./tutorial_pages/seed.qmd) – How can you generate the same random numbers?
 * [Sample size `n`](./tutorial_pages/sample-size-n.qmd) – How many values should you generate within a simulation?
 * [Number of simulations `nrep`](./tutorial_pages/number-of-simulations-nrep.qmd) – How many repeats of a simulation should you run?
-* [Dry rule](./tutorial_pages/dry-rule.qmd) – How to write your own functions?
+* [DRY rule](./tutorial_pages/dry-rule.qmd) – How to write your own functions?
 * [Simulate to check alpha](./tutorial_pages/check-alpha.qmd) – Write your first simulation and check the rate of false-positive findings.  
 * [Simulate to check power](./tutorial_pages/check-power.qmd) – Simulate data to perform a power analysis.  
 * [Simulate to prepare a preregistration](./tutorial_pages/simulate-for-preregistration.qmd) – Simulate data to test statistical analyses before preregistering them.  

index.qmd

@@ -31,7 +31,7 @@ It is necessary that you work through the sections of the tutorial in order. Ple
 * [Setting the seed](./tutorial_pages/seed.qmd) – How can you generate the same random numbers?
 * [Sample size `n`](./tutorial_pages/sample-size-n.qmd) – How many values should you generate within a simulation?
 * [Number of simulations `nrep`](./tutorial_pages/number-of-simulations-nrep.qmd) – How many repeats of a simulation should you run?
-* [Dry rule](./tutorial_pages/dry-rule.qmd) – How to write your own functions?
+* [DRY rule](./tutorial_pages/dry-rule.qmd) – How to write your own functions?
 * [Simulate to check alpha](./tutorial_pages/check-alpha.qmd) – Write your first simulation and check the rate of false-positive findings.  
 * [Simulate to check power](./tutorial_pages/check-power.qmd) – Simulate data to perform a power analysis.  
 * [Simulate to prepare a preregistration](./tutorial_pages/simulate-for-preregistration.qmd) – Simulate data to test statistical analyses before preregistering them.  

tutorial_pages/check-alpha.qmd

@@ -51,9 +51,9 @@ These proportions are not significantly different from 5%.
 prop.test(45, 1000, p = 0.05, alternative = "two.sided", correct = TRUE)
 ```
 
-|  1-sample proportions test with continuity correction  
-|  data:  45 out of 1000, null probability 0.05  
-|  X-squared = 0.42632, df = 1, p-value = 0.5138  
+> 1-sample proportions test with continuity correction  
+> data:  45 out of 1000, null probability 0.05  
+> X-squared = 0.42632, df = 1, p-value = 0.5138  
 
 It is important to note that, although `alpha = 0.05` is commonly used, this is an arbitrary choice and you should consider what is an appropriate type 1 error rate for your particular investigation.  
 

tutorial_pages/check-power.qmd

@@ -34,9 +34,8 @@ If we sample values from two normal distributions with different means (e.g. N(0
 **YOUR TURN:**  
 1. Use your simulation skills to work out the power through simulation.
 Write a function that does the following: 
-
-i) Draws `n` values from a random normal distribution with `mean1` and another `n` values from a normal distribution with `mean2`.
-ii) Compares the means of these two samples with a *t*-test and extracts the *p*-value.
+    i) Draws `n` values from a random normal distribution with `mean1` and another `n` values from a normal distribution with `mean2`.
+    ii) Compares the means of these two samples with a *t*-test and extracts the *p*-value. 
 2. Replicate the function 1000 times using the parameters used in the power calculation above (that used the `power.t.test()` function). 
 3. Calculate the proportion of *p*-values that are smaller than 0.05.
 

tutorial_pages/dry-rule.qmd

@@ -2,7 +2,6 @@
 
 ## *vs.* **W**rite **E**verything **T**wice – WET rule
 
-<br/>
 Following the WET rule:  
 
 * Makes changes more difficult and/or time consuming.  

tutorial_pages/random-numbers-generators.qmd

@@ -9,7 +9,7 @@ Sampling without replacement means that when you repeatedly draw e.g. one item a
 
 ***
 **YOUR TURN:**  
-Sample 100 values between 3 and 103 with replacement. For this, open the file `./exercise_script.R` from the root of your local repository (with or without answers), review the examples if needed, complete the exercise, and check out the proposed answer.
+Sample 100 values between 3 and 103 with replacement. For this, open the R script(s) with the exercises (`./exercise_script_with_solutions.R` and/or `./exercise_script_without_solutions.R`) from the root of your local repository, review the examples if needed, complete the exercise, and check out the proposed answer.
 
 ***
 

tutorial_pages/real-life-example.qmd

@@ -9,8 +9,6 @@ I created this code while preparing my preregistration for a simple behavioural
 
 The R script screenshot below, `glm_Freq_vs_YN.R`, can be found in the folder [Ihle2020](https://github.com/lmu-osc/Introduction-Simulations-in-R/tree/main/Ihle2020).  
 
-<br/>
-
 This walkthrough will use the steps as defined on the page '[General structure](./general-structure.qmd)'.
 
 

tutorial_pages/repeat.qmd

@@ -1,8 +1,6 @@
 # Repetition
 
-The function 
-
-* `replicate(nrep, expression)` repeats the `expression` provided `nrep` times.
+The function `replicate(nrep, expression)` repeats the `expression` provided `nrep` times.
 
 For example, `replicate(10, mean(rnorm(100)))` reads: 'Draw 100 values from a normal distribution with a mean of 0 and a standard deviation of 1 (the default values of `rnorm(n, mean, sd)`), calculate the mean of these 100 values, and do all that 10 times.'