flannery feedback

lessons/Data-Science/dot-plots/langs/en-us/index.adoc

@@ -32,6 +32,8 @@
 
 @material-links
 
+| Preparation
+
 
 |===
 
@@ -47,20 +49,23 @@ Students create and interpret dot plots, learning new vocabulary to informally d
 
 === Launch
 
-@teacher{Draw or project a number line on a piece of chart paper or on the board. Your number line should start at zero and go up to 15 by ones. If you have a student with a name that is more than 15 letters, extend the number line accordingly.}
+@teacher{Before class, decide if you want your students to create a communal dot plot (1) via live survey, or (2) via each student drawing their own data point on a shared display.
 
-@lesson-instruction{
+If you opt to do the live survey... FILL THIS IN.
 
-@image{images/number-line.png}
+If you opt to have each student draw a data point:  Draw or project a number line on a piece of chart paper or on the board. Your number line should start at zero and go up to 15 by ones. If you have a student with a name that is more than 15 letters, extend the number line accordingly.}
+
+@lesson-instruction{
 
 - Count how many letters are in your first name.
-- Once you have counted, line up at the board to draw a dot above the number of letters in your first name. You may stack dots, but try to keep them evenly spaced.
-- Once you return to your desk, copy the class dot plot onto the top section of @printable-exercise{create-interpret-dot-plots.adoc}
-}
+- Once you have counted, follow your teachers' instructions to do one of the following:
+** Complete the live survey and watch our class data visualization appear and evolve.
+** Line up at the board to draw a dot above the number of letters in your first name. You may stack dots, but try to keep them evenly spaced.
 
-@QandA{
-@Q{What do you Notice about the data that we have collected and visualized? What do you Wonder about this data and its visualization?}
-@A{Students will likely use informal language to describe the distribution of data. During the lesson, students will learn and practice using formal vocabulary for describing distributions.}
+@image{images/number-line.png}
+
+- Congratulations! Your individual name length is now represented in our class dot plot.
+- Copy the class dot plot onto the top section of @printable-exercise{create-interpret-dot-plots.adoc}. We will discuss our class data visualization later in the lesson.
 }
 
 @strategy{Dot Plots?!}{
@@ -71,16 +76,18 @@ Students are generally successful interpreting dot plots (compared to, say, box
 To combat this challenge, @citation{bakker-et-al-2005, "Bakker, Biehler, and Konold (2005)"} recommend building a strong foundation with data visualizations where _individual cases are visible_. In short: don't gloss over dot plots! When introducing dot plots and histograms, the research recommends pairing the less-familiar aggregate data visualizations with their corresponding (familiar) dot plots as we do in this lesson and others.
 }
 
+
 === Investigate
 
+
 @lesson-instruction{
-- Complete the second section ("Reading a Dot Plot") of @printable-exercise{create-interpret-dot-plots.adoc}.
+- Complete the first section ("Reading a Dot Plot") of @printable-exercise{interpret-dot-plots.adoc}.
 - Be prepared to discuss your answers with the class.
 }
 
-@teacher{Review students' responses as a class. Questions 1, 2, and 3 touch on three relevant concepts: range, mode, and proportional reasoning.}
+@teacher{Review students' responses as a class. Questions 1, 2, and 3 touch on three relevant concepts: range, mode, and proportional reasoning. Question four gets students thinking about gaps, which are discussed in the next section of the worksheet.}
 
-Now that we are comfortable creating dot plots, we need a common vocabulary to discuss the data that they display. To describe the distribution of data--the way that it is spread out on a number line--it is helpful to locate any outliers, clusters, peaks, and gaps.
+Now that we are comfortable reading dot plots, we need a common vocabulary to discuss the data that they display. To describe the distribution of data--the way that it is spread out on a number line--it is helpful to locate any outliers, clusters, peaks, and gaps.
 
 - A *cluster* is a group of data points that are close together.
 - A *gap* is an interval where there are no data points.
@@ -91,7 +98,7 @@ Now that we are comfortable creating dot plots, we need a common vocabulary to d
 
 @center{@image{images/names1.png, 250}}
 
-- Let's label the clusters, gaps, outliers, and peaks on dot plot A (question 4) on @printable-exercise{create-interpret-dot-plots.adoc}.
+- Let's label the clusters, gaps, outliers, and peaks on the dot plot in the first section of @printable-exercise{interpret-dot-plots.adoc}.
 ** There is a peak at 4.
 ** There is a cluster from 3 to 6.
 ** There are gaps at 7 and 10.
@@ -135,6 +142,12 @@ In question 7 on @printable-exercise{create-interpret-dot-plots.adoc}, we ask st
 @teacher{Review students' responses, emphasizing that there are multiple ways to decide what is typical in a dataset. You may want to highlight a few different and appropriate responses to highlight that we are simply _estimating_ typicality.}
 
 
+@QandA{
+@Q{What do you Notice about the data that we have collected and visualized? What do you Wonder about this data and its visualization?}
+@A{Students will likely use informal language to describe the distribution of data. During the lesson, students will learn and practice using formal vocabulary for describing distributions.}
+}
+
+
 === Synthesize
 
 @QandA{

lessons/Data-Science/dot-plots/langs/en-us/pages/interpret-dot-plots.adoc

@@ -0,0 +1,77 @@
+= Interpreting Dot Plots
+
+== Reading a Dot Plot
+
+The dot plot on below is a name length data visualization created by a group of 25 students.
+
+@vspace{1ex}
+
+@center{@image{../images/names1.png, 300}}
+
+@n What is the difference (in letters) between the longest and shortest name? @fitb{}{}
+
+@n What is the most common name length?  @fitb{}{}
+
+@n What fraction of students have first names that are 5 letters long? @fitb{}{}
+
+@n True or False: No students have 10-letter names. @fitb{}{@ifsoln{True}}
+
+
+@n The distribution of the data is the way that it is spread out on the number line. One way to describe distribution is by identifying peaks, clusters, gaps, and outliers. As a class, label any peaks, clusters, gaps, or outliers on the dot plot *above*.
+
+
+== Interpreting Peaks, Clusters, Gaps, and Outliers
+
+
+@n Let's think about what those peaks, clusters, gaps and outliers *tell* us about the dataset. In the dot plot above:
+
+- the peak indicates that @fitb{1em}{@ifsoln{4}} letters is the most common name length
+- the cluster indicates that many students' names are @fitb{1em}{@ifsoln{3-6}} letters
+- the gaps tell us that, in this sample, no students have names that are @fitb{1em}{@ifsoln{7}} letters or @fitb{1em}{@ifsoln{10}} letters
+- the outlier is @fitb{1em}{@ifsoln{11}} letters, telling us that longer names are uncommon in this sample.
+
+
+@n The dot plot below represents the name lengths of a different group of 25 students. What you can conclude about the dataset based on its peaks, clusters, gaps, and outliers?
+
+@vspace{1ex}
+
+
+[cols="1a,2a"]
+|===
+
+|
+@center{@image{../images/names2.png, 300}}
+
+|
+@fitb{}{}
+
+@fitb{}{}
+
+@fitb{}{}
+
+@fitb{}{}
+
+|===
+
+
+== Typicality of Name Length Data
+
+
+@n Would 7.5 letters be a good description of the number of letters in students' names in your class? Why or why not? @fitb{}{@ifsoln{Responses will vary.}}
+
+@fitb{}{@ifsoln{Emphasize for students that the middle of the x-axis is not necessary what's typical in a dataset.}}
+
+@fitb{}{}
+
+@n What do you think is a typical value in this dataset? (There will likely be more than one correct response.) Explain your reasoning. @fitb{}{}
+
+@fitb{}{}
+
+@fitb{}{}
+
+
+@n Identify another value someone else might claim is typical in this sample. Why would they choose that value? @fitb{}{}
+
+@fitb{}{}
+
+@fitb{}{}