X-Git-Url: https://code.communitydata.science/stats_class_2020.git/blobdiff_plain/1c7b8b613996293fe6f47c598226c8ec4a2b142b..c13bce81edb9862158e4da1becb092faa0c1acb1:/assessment/interactive_assessment.rmd

diff --git a/assessment/interactive_assessment.rmd b/assessment/interactive_assessment.rmd
index e81b938..a1e3d8c 100644
--- a/assessment/interactive_assessment.rmd
+++ b/assessment/interactive_assessment.rmd
@@ -134,8 +134,8 @@ zeroToOneRescaler <- function() {
 }
 
 test_vector = c(1,2,3,4,5)
-zeroToOneRescaler(test_vector)
 # Should print c(0, 0.25, 0.5, 0.75, 1.00)
+zeroToOneRescaler(test_vector)
 ```
 
 ```{r R_debug1-solution}
@@ -146,8 +146,8 @@ zeroToOneRescaler <- function(x) {
 }
 
 test_vector = c(1,2,3,4,5)
-zeroToOneRescaler(test_vector)
 # Should print c(0, 0.25, 0.5, 0.75, 1.00)
+zeroToOneRescaler(test_vector)
 ```
 
 ```{r R_debug1-response}
@@ -283,16 +283,16 @@ quiz(
     answer("if an effect is causal or not.")
   ),
   question("A distribution that is right-skewed has a long tail to the:",
-    answer("right", correct = TRUE),
-    answer("left")
+    answer("right.", correct = TRUE),
+    answer("left.")
   ),
   question("A normal distribution can be characterized with only this many parameters:",
-    answer("1"),
-    answer("2", correct = TRUE),
-    answer("3")
+    answer("1."),
+    answer("2.", correct = TRUE),
+    answer("3.")
   ),
   question("When we calculate standard error, we calculate",
-    answer("using a different formula for every type of variable."),
+    answer("it using a different formula for every type of variable."),
     answer("the sample standard error, which is an estimate of the population standard error.", correct = TRUE),
     answer("whether or not our result is causal.")
   ),
@@ -304,7 +304,7 @@ quiz(
   question("P values tell us about",
     answer("the world in which our null hypothesis is true.", correct = TRUE),
     answer("the world in which our null hypothesis is false."),
-    answer("the world in which our data describe a causal effect")
+    answer("the world in which our data describe a causal effect.")
   ),
   question("P values are",
     answer("a conditional probability.", correct = TRUE),
@@ -325,10 +325,9 @@ quiz(
 
 ```{r StatsConcepts_sampling}
 quiz(
-  question("A political scientist is interested in the effect of government type on economic development.
-She wants to use a sample of 30 countries evenly represented among the Americas, Europe,
-Asia, and Africa to conduct her analysis. What type of study should she use to ensure that
-countries are selected from each region of the world? Assume a limitied research budget.",
+  question("A political scientist is interested in the effect of teaching style type on standardized test performance
+She wants to use a sample of 30 classes evenly represented among the Communication, Computer Science, and Business to conduct her analysis. What type of study should she use to ensure that
+classes are selected from each region of the world? Assume a limited research budget.",
     answer("Observational - simple random sample"),
     answer("Observational - cluster"),
     answer("Observational - stratifed", correct=TRUE),
@@ -537,7 +536,11 @@ $Q_1 - 1.5 \times IQR, \quad Q_3 + 1.5 \times IQR$
 ## Answer Report
 Finally, let's generate a report that summarizes your answers to this evaluation.
 
-Answers are written to a file that looks like this: `question_submission-{CURRENT TIME}.csv`. They're also saved in R Studio's global environment as a variable called `df`. Run the below code chunk to see what `df` looks like.
+Answers are written to a file that looks like this: `question_submission-{CURRENT TIME}.csv`. 
+
+Take note of this csv file: this is what you will submit to Canvas.
+
+They're also saved in R Studio's global environment as a variable called `df`. Run the below code chunk to see what `df` looks like.
 
 ```{r report1, exercise=TRUE}
 df