In a Histogram, What the Class Intervals

How to prepare for test 1  Have clear understanding of concepts, definitions, formulas, notations   Read the lecture notes (first page gives important concepts) at least 5 times  Review quizzes Excel skills  Review homework assignments  Review the course syllabus Read the book at least 3 times  Do exercises recommended (listed on page 1 of each topic)

To do well in test 1, you must know and understand the following concepts. Note: You can find the answers to the following questions by studying the lecture notes at least 5 times and studying the textbook at least 3 times.  Need help? Stop by your instructor’s office 

Population, Sample  What is a population? Give two examples.  What is a sample? Give two examples.  Explain the differences between a sample and a population.  Able to identify the population and the sample of a statistical study   Explain how population and variables differ.  Explain how populations and samples differ.

Variable, Data  What is a variable?  Define qualitative variable. Provide two examples  Define quantitative variable. Provide two examples  Discuss the difference between discrete and continuous variables.  You must be able to discrete and continuous variables and data.  Data  What are data?  You must be able to group data into a frequency distribution and a relative-frequency distribution.  Briefly describe the difference between categorical data and numerical data.  Explain the difference between quantitative and qualitative data. 

Frequency distribution  What is a frequency distribution?  What is class frequency?  What is class relative frequency?  What are the rules for constructing a frequency distribution?  Give one disadvantage of frequency distribution tables.  Explain the difference between each of the following pairs of terms: Class frequency and class relative frequency  Percentage and class relative frequency   What conditions indicate that we should use relative frequency distributions rather than frequency distributions?  Graphical displays You must know how to construct, read, and interpret graphical displays and know which ones are appropriate for which types of data.

Bar graphs (Bar graphs, time-series plots, pie charts, histograms)  What kind of data can bar graphs show?  What is the difference between a frequency bar graph and a relative-frequency bar graph?   Know how to use Excel to construct a bar graph.

Time-series plot  What kind of data can time-series plots show?  1 Histograms  What kind of data can histograms show?  In a histogram, what are the class intervals?  How many classes are recommended in a histogram for a data set with more than 50 observations?  Explain the difference between a frequency histogram and a relative-frequency histogram.   Know how to describe the shape of distribution of a data set from a histogram.  List two differences between a histogram and a bar graph.   Know how to use Excel to construct histograms.

Box plot  What is a box plot?  How is the box plot constructed?  Know how to describe the shape of distribution of data from a box plot.  What are the five values needed to draw a box plot?  What do the various parts of a box plot for a sample represent? Describe the interpretation of each feature. In particular, describe how the plot “calibrates” outliers?  How do you determine the upper whisker?  How do you determine the lower whisker?  Are there any differences between a box plot and a histogram?   Are there any similarities between a box plot and a histogram? 

Numerical summary [mean, median, SD]  You must be able to recognize data for which the mean is not appropriate.  Does the size of the numbers in a distribution have any effect on the mean?  Under what condition is the median a better measure of the center of a data set than is the mean?   The interquartile range and the standard deviation are two different measures of spread. Which measure do you think is more affected by outliers? Explain.  Give three different measures of central tendency.  Explain the difference between a measure of central tendency and a measure of variability.

Sampling techniques  What are some reasons why a decision maker would choose to take a sample rather than a census?  A random sample may be very difficult to obtain. Why?  What is simple random sampling?  What is a simple random sample?  Why is the random sample so important in statistics?  What conditions are required in order for a sample to be a random sample?  What is a sampling frame?  The telephone book might not be a representative sampling frame. Explain why.  What are the four random sampling methods?  What are the differences between an observational study and an experiment (randomized controlled experiment)?

Study the following examples in textbook:

Chapter 1: Examples 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 1.10, 1.11

Chapter 3: Examples 3.1, 3.2, 3.3, 3.4, 3.6, 3.7, 3.12, 3.13, 3.14, 3.15, 3.16, 3.17, 3.19

Chapter 4: Examples 4.1, 4.2, 4.4, 4.5, 4.7, 4.8, 4.10, 4.11, 4.12, 4.13, 4.14