Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 1 of 20 Chapter 1 Section 1 Introduction to the Practice of Statistics

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 2 of 20 Chapter 1 – Section 1 ●Learning objectives  Define statistics and statistical thinking  Understand the process of statistics  Distinguish between qualitative and quantitative variables  Distinguish between discrete and continuous variables

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 3 of 20 Chapter 1 – Section 1 ●Learning objectives  Define statistics and statistical thinking  Understand the process of statistics  Distinguish between qualitative and quantitative variables  Distinguish between discrete and continuous variables

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 4 of 20 Chapter 1 – Section 1 ●The science of statistics is  Collecting  Organizing  Summarizing  Analyzing information to draw conclusions or answer questions

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 5 of 20 Chapter 1 – Section 1 ●Anecdotal claims, as opposed to statistics, are  Conclusions based on very little data  Stories and rumors ●Anecdotal claims, as opposed to statistics, are  Conclusions based on very little data  Stories and rumors ●Data can be misused when  Data is incorrectly obtained  Data is incorrectly analyzed ●Anecdotal claims, as opposed to statistics, are  Conclusions based on very little data  Stories and rumors ●Data can be misused when  Data is incorrectly obtained  Data is incorrectly analyzed ●Good statistics should  Understand the difference between direct and indirect (lurking variable) relations  Understand the impacts of variability

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 6 of 20 Chapter 1 – Section 1 ●Statistics and mathematics have similarities but are different ●Mathematics  Solves problems with 100% certainty  Has only one correct answer ●Statistics, because of variability  Does not solve problems with 100% certainty (95% certainty is much more common)  Frequently has multiple reasonable answers

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 7 of 20 Chapter 1 – Section 1 ●Learning objectives  Define statistics and statistical thinking  Understand the process of statistics  Distinguish between qualitative and quantitative variables  Distinguish between discrete and continuous variables

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 8 of 20 Chapter 1 – Section 1 ●A population  Is the group to be studied  Includes all of the individuals in the group ●A population  Is the group to be studied  Includes all of the individuals in the group ●A sample  Is a subset of the population  Is often used in analyses because getting access to the entire population is impractical

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 9 of 20 Chapter 1 – Section 1 ●Identify the research objective  What questions are to be answered?  What group should be studied? ●Identify the research objective  What questions are to be answered?  What group should be studied? ●Collect the information needed  Can you access the entire population?  How can you collect a good sample?  What other methods are available and appropriate?

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 10 of 20 Chapter 1 – Section 1 ●Organize and summarize the information  Descriptive statistics (chapters 2 through 4)  Visual methods such as charts and graphs  Numeric methods such as calculations ●Organize and summarize the information  Descriptive statistics (chapters 2 through 4)  Visual methods such as charts and graphs  Numeric methods such as calculations ●Draw conclusions from the information  Inferential statistics (chapters 8 through 15)  Various methods that are appropriate for different questions and different types of data sets

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 11 of 20 Chapter 1 – Section 1 ●An example of a statistical study ●State the research objective – determine the effectiveness of a antihypertensive drug ●An example of a statistical study ●State the research objective – determine the effectiveness of a antihypertensive drug ●Collect the information – divide 1,317 patients into two groups with two different treatments ●An example of a statistical study ●State the research objective – determine the effectiveness of a antihypertensive drug ●Collect the information – divide 1,317 patients into two groups with two different treatments ●Organize the information – measure blood pressure data ●An example of a statistical study ●State the research objective – determine the effectiveness of a antihypertensive drug ●Collect the information – divide 1,317 patients into two groups with two different treatments ●Organize the information – measure blood pressure data ●Draw the conclusions – extend the study results to conclusions about the entire population

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 12 of 20 Chapter 1 – Section 1 ●Learning objectives  Define statistics and statistical thinking  Understand the process of statistics  Distinguish between qualitative and quantitative variables  Distinguish between discrete and continuous variables

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 13 of 20 Chapter 1 – Section 1 ●Characteristics of the individuals under study are called variables  Some variables have values that are attributes or characteristics … those are called qualitative or categorical variables  Some variables have values that are numeric measurements … those are called quantitative variables ●The suggested approaches to analyzing problems vary by the type of variable

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 14 of 20 Chapter 1 – Section 1 ●Examples of qualitative variables  Gender  Zip code  Blood type  States in the United States  Brands of televisions ●Qualitative variables have category values … those values cannot be added, subtracted, etc.

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 15 of 20 Chapter 1 – Section 1 ●Examples of quantitative variables  Temperature  Height and weight  Sales of a product  Number of children in a family  Points achieved playing a video game ●Quantitative variables have numeric values … those values can be added, subtracted, etc.

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 16 of 20 Chapter 1 – Section 1 ●Learning objectives  Define statistics and statistical thinking  Understand the process of statistics  Distinguish between qualitative and quantitative variables  Distinguish between discrete and continuous variables

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 17 of 20 Chapter 1 – Section 1 ●Quantitative variables can be either discrete or continuous ●Discrete variables  Variables that have a finite or a countable number of possibilities  Frequently variables that are counts ●Quantitative variables can be either discrete or continuous ●Discrete variables  Variables that have a finite or a countable number of possibilities  Frequently variables that are counts ●Continuous variables  Variables that have an infinite but not countable number of possibilities  Frequently variables that are measurements

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 18 of 20 Chapter 1 – Section 1 ●Examples of discrete variables  The number of heads obtained in 5 coin flips  The number of cars arriving at a McDonald’s between 12:00 and 1:00  The number of students in class  The number of points scored in a football game ●The possible values of qualitative variables can be listed

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 19 of 20 Chapter 1 – Section 1 ●Examples of continuous variables  The distance that a particular model car can drive on a full tank of gas  Heights of college students ●Sometimes the variable is discrete but has so many close values that it could be considered continuous  The number of DVDs rented per year at video stores  The number of ants in an ant colony

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 1 – Slide 20 of 20 Summary: Chapter 1 – Section 1 ●The process of statistics is designed to collect and analyze data to reach conclusions ●Variables can be classified by their type of data  Qualitative or categorical variables  Discrete quantitative variables  Continuous quantitative variables