1. Warm Up

2. Unit 2: One-Variable Statistics

3. Two Main Uses of Statistics TO DESCRIBE (Data Analysis) TO PREDICT (Statistical Inference)

4. Definitions Data: A collection of information in context. Population: A set of individuals that we wish to describe and/or make predictions about. Individual: Member of a population. Variable: Characteristic recorded about each individual in a data set.

5. Types of Variables Categorical Variable: A variable that records qualities or characteristics of an individual, such as gender or eye color. Quantitative Variable: A variable that measures a characteristic of an individual, such as height, weight, or age. In this unit, we will focus on quantitative data.

6. What type of data is it? CategoricalQuantitative Deals with numbers. Quantitative → Quantity Data which can be measured. Length, height, area, volume, weight, speed, time, temperature, humidity, sound levels, cost, members, ages, etc. Deals with descriptions. Data can be observed but not measured. Colors, textures, smells, tastes, appearance, beauty, etc. Qualitative → Quality

7. Categorical or Quantitative Data? Birth month Number of siblings Height in inches Average amount of time (in minutes) of your ride to school. Number of pets model of the car you drive (or dream car ) Age of your youngest parent Predicted letter grade of your first Special Topics test.

8. 1. Brand of vehicle purchased by a customer 2. Price of a CD 3. Number of students in a class of 30 who prefer peanut M&Ms over plain M&Ms 4. Phone number of all the students enrolled in school. 5. The height of a 1 year old child. 6. Number of students in a class of 35 who turn in a term paper before the due date. 7. Gender of the next baby born at a particular hospital. 8. Amount of fluid (oz) dispensed by a machine used to fill bottles with soda. 9. Thickness of the gelatin coating of a Vitamin C capsule 10. Brand of computer purchased by a customer 11. State of birth for someone born in the United States. 12. Price of a textbook 13. The phone numbers of everyone in this class. 14. Actual weight of coffee in a one pound can. 15. The length of a rattlesnake.

9. Describing Data Two ways to describe data: Graphically Numerically

10. Dotplot Histogram Boxplot Describing Data Graphically

11. Frequency Tables & Histograms

12. Link Up! How many paperclips can you hook together in 60 seconds? Frequency DistributionHistogram Paper Clips Linked TallyFrequency 0-5 5-10 10-15 15-20 20-25 25-30 30-35 What’s the difference between a bar graph and a histogram?

13. Describing Distributions Shape Center Spread Outliers

14. Shape Mound shaped & symmetrical Skewed left (extreme low values) Skewed right (extreme high values) Uniform

15. Center When describing a distribution at first, the center can be “eyeballed.” Remember, you are trying to answer the question: “What is the most typical value?”

16. Spread Range Remember, you are trying to answer the question: “ How much do values typically vary from the center?” BE SURE TO STATE EVERYTHING IN CONTEXT!!

17. NFL Rushing Statistics Group activity: Make a frequency distribution table for your assigned column of data. Draw the corresponding histogram on graph paper. Write a paragraph about your data that addresses shape, center, spread, and outliers.

20. Dotplot: Button Activity You will be collecting and organizing the amount of buttons you and your classmates have on your clothes. 1.Set up a number line to record your data. Where should it start? How far should it go? What should the scale be? 2.Take 3-5 minutes to circulate and record your data directly on the number line you just created to form the dot plot. You should ask at least 10 of their classmates. 3.Write a description of the button data (shape, center, spread, outliers). Let’s share!

21. Coming up… HW 2.1 QUIZ – Monday or Tuesday Unit 2 TEST – Friday September 20 th