1. Learning Journal Reflective Comments:

You should date each entry, and use clear titles and sub-headings.These entries should be brief, direct sentences indicating quick comments or notes such as:

* when you completed each step in the Learning Guide during the week,

* any problems or unexpected events that occurred during the week (including problems understanding new or old material), and

* any other noteworthy that might affect your performance in this class.

There is no need to include personal information or details of family events, but be sure to mention the existence of any situations that will positively or negatively affect your ability to focus on the classwork.

2. Vocabulary and R functions

a) What does the symbol x-bar represent?

b) What does the Greek lettermu() represent as it was used in this week's lessons?

c) What is the difference between x-bar and mu?

3. Mean

a) Many people already know how to find the mean (average) of a sample of data by "adding all the numbers and dividing by the number of values in the dataset."

4, and then describe, another method of finding the mean by using the sample space

List of seven, 2-digit numbers (with no duplicates) and another set of seven probabilities (with no duplicates).The probabilities must add to 1.

Open R, and manually enter those numbers and their corresponding probabilities to calculate the mean using only addition and multiplication (in other words, enter only the numbers, the plus sign, and the * for multiplication, like on the bottom of Yakir, 2011, p. 57).Paste all the R output into your learning journal.

b) Describe what your calculation is doing and what the answer means.

In the previous chapters we examined the variability in data. In the statisti- cal context, data is obtained by selecting a sample from the target population and measuring the quantities of interest for the subjects that belong to the sample. Different subjects in the sample may obtain different values for the measurement, leading to variability in the data.

This variability may be summarized with the aid of afrequency table, a table ofrelative frequency, or via thecumulative relative frequency. A graphical display of the variability in the data may be obtained with the aid of thebar plot, thehistogram, or thebox plot.

Numerical summaries may be computed in order to characterize the main features of the variability. We used themeanand themedianin order to identify the location of the distribution. Thesample variance, or better yet thesample standard deviation, as well as theinter-quartile rangewere all described as tools to quantify the overall spread of the data.