1. What is Statistics?

2.  Art and Science of dealing with data.  Data: numbers with a context (units)…makes it informative.  Context engages our background knowledge and allows us to make judgments about the significance of the number.  Uses data to gain insight and draw conclusions.

3.  Sports  Healthcare professionals.  Public policy, and many different fields of study.  Managers (efficient crunching of numbers results in a better bottom line).  Scientists/Engineers  This list could go on and on

4. 1. Producing Data 2. Organizing and Describing Data 3. Chance 4. Inference

5.  Describes methods for producing data which can give clear answers to specific questions.  Where the data comes from is important… Learn how to select samples and design.  Experiments are very influential in statistics.  Example – Opinion polls, clinical trials, etc…

6.  Methods and strategies for exploring, organizing and describing data.  Using graphs and numerical summaries.  Learn how to look at data intelligently.

7.  Probability  Variation  Risk

8.  Moves beyond the data to draw conclusions.  Take into account that variation is everywhere  Conclusions can be uncertain.

9.  When we talk about data, a big part of stats is deciding what to measure in order to produce data that helps answer your questions.  Need a clear objective before collecting data.  Measurements are made on individuals and organized in variables.

10.  What do these number mean to you?  The birth weights of my kids  The mean nothing without units  9.6 pounds and 9.0 pounds

11.  Individuals – the objects described by a set of data Ex – people, animals, things  Variable – any characteristic of an individual Can take different values for different individuals. Although Statistics deals with numbers. Not all variables are numerical. To use Statistics with other (non-numerical) variables we use counts or percents.

12.  Quantitative variables – numerical values (you can perform any type of arithmetic with these) Ex – test scores, age, salaries, etc…  Categorical variables – use percents or counts; places an individual into one or several groups or categories Ex – grade level, class, eye color

14.  Individuals - ◦ Students in class  Variables – 1. ID (categorical) 2. Grade Level (categorical, not numerical…Fresh, Soph, Junior, Senior OR 9, 10, 11, 12) 3. Gender (categorical) 4. HR (categorical) 5. Counselor (categorical) 6. Test 1 (numerical/quantitative)

15.  1. Textbook: Pgs. 7&8 #1-4  2. Data collection sheet  3. Celtics examples