CHAPTER 1 –PICTURING DISTRIBUTIONS WITH GRAPHS - DESCRIPTIVE STATISTICS

TOPICS COVERED - Sections shown with numbers as in e-book

Any topic listed on this document and not covered in class must be studied “On Your Own” (OYO)

Get into my website – Click on the OIRA link – Click on Student Data – Click on 2011 Student Profile

Explore pages 1, 5, 9, 10, 11, 13, 21 to introduce the vocabulary in the chapter

Section 1.1 – INDIVIDUALS AND VARIABLES (pg. 3)

  • Individuals
  • Variable
  • Categorical or qualitative variable
  • Quantitative variable (include unit of measurement)

Section 1.2 – CATEGORICAL VARIABLES (pg. 6)

  • Graphs for categorical variables
  • Bar graphs
  • Pie graphs
  • Clustered bar graph – display trends (example: data from MC students for different years)
  • Distribution of a Variable
  • Values: categories
  • Frequencies or percents
  • Importance of “OTHER” category
  • Is this necessary when constructing a bar graph?
  • Is this necessary when constructing a pie graph?
  • Demonstrate use of EXCEL for graphing categorical variables

Select any of the examples or problems in chapter 1 to construct a pie graph and a bar graph using EXCEL.

The steps have been outlined below for the following:

Example 1.2 –page 7 –Fields of study – Get into the e-book

  • Click on DATA SET
  • Select EXCEL
  • Save document
  • Highlight the distribution (including title)
  • Click on INSERT (top)
  • Insert a PIE GRAPH (after creating the graph, add % by clicking the appropriate one)
  • Select the distribution again and paste it below
  • Select the distribution without including titles and arrange percents in decreasing order (click on DATA (top) and sort by decreasing %)
  • Select distribution with title and INSERT a BAR GRAPH

Section 1.3 – QUANTITATIVE VARIABLES (pg. 11)

  • Histograms
  • Classes
  • Frequencies or counts
  • Relative frequencies (% written as decimals)

Section 1.4 – INTERPRETING HISTOGRAMS (pg. 15)

  • Describe overall pattern
  • Shape
  • Symmetric
  • Skewed to the right
  • Skewed to the left
  • Center (more about this in chapter 2)
  • Spread (more about this in chapter 2)
  • Describe deviations from the pattern
  • Outliers
  • Demonstrate use of CRUNCH IT – get into the e-book

Example 1.7 – page 17 – Who takes the SAT?

  • Click on CRUNCH IT
  • Select GRAPHICS
  • Select HISTOGRAM
  • Select the variable PctSAT
  • Select FREQUENCY
  • Leave OPTIONAL PARAMETERS blank
  • Click OK
  • What is the shape of the histogram?
  • Now try again: fill in the OPTIONAL PARAMETERS to obtain the histogram shown in the book
  • To obtain the one on the book, use 5 bins, width of 20, starting at 0
  • If you want you can Right click on graph, copy and paste in a word document
  • Try the stem and leaf plot and read the next section to understand the graph

Section 1.5 – QUANTITATIVE VARIABLES – STEM PLOTS (pg. 19)

  • Stem plots
  • Stem
  • Leaf
  • Split stem and leaf plot
  • Back to back stem and leaf plot

Section 1.6 – TIME PLOTS (pg. 23)

  • Time plots
  • Time horizontal axis
  • Variable in vertical axis
  • Reveals
  • Trends
  • Cycles
  • To construct using CRUNCH IT, use Line Plot
  • To construct using EXCEL, use a connected scatter-diagram

Friday’s quiz will be similar to the STATS PORTAL ASSIGNMENT - STATS@WORK

Picture This - Which graph is appropriate? - Mindy Admin

I have pasted the Chapter 1 Summary found on the e-book

Do the same with the other chapters

Add your own summarized notes and use the document to review on a daily basis

CHAPTER 1 SUMMARY – Copied and pasted from the e-book

  • A data set contains information on a number of individuals.Individuals may be people, animals, or things. For each individual, the data give values for one or more variables. A variable describes some characteristic of an individual, such as a person’s height, sex, or salary.
  • Some variables are categorical and others are quantitative. A categorical variable places each individual into a category, such as male or female. A quantitative variable has numerical values that measure some characteristic of each individual, such as height in centimeters or salary in dollars.
  • Exploratory data analysis uses graphs and numerical summaries to describe the variables in a data set and the relations among them.
  • After you understand the background of your data (individuals, variables, units of measurement), the first thing to do is almost always plot your data.
  • The distribution of a variable describes what values the variable takes and how often it takes these values. Pie charts and bar graphs display the distribution of a categorical variable. Bar graphs can also compare any set of quantities measured in the same units. Histograms and stemplots graph the distribution of a quantitative variable.
  • When examining any graph, look for an overall pattern and for notable deviations from the pattern.
  • Shape, center, and spread describe the overall pattern of the distribution of a quantitative variable. Some distributions have simple shapes, such as symmetric or skewed. Not all distributions have a simple overall shape, especially when there are few observations.
  • Outliers are observations that lie outside the overall pattern of a distribution. Always look for outliers and try to explain them.
  • When observations on a variable are taken over time, make a time plot that graphs time horizontally and the values of the variable vertically. A time plot can reveal trends, cycles, or other changes over time.