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Transcript of Chapter 1.1
Outliers 1.1 Analyzing Displays for Categorical Variables Frequency Table
Relative Frequency Table
Bar Graphs/ Bar Charts
Pie Charts Data Analysis
Who, What, Why, When, Where & How?
*pg 2 Organize, Display, Summarize and ask Questions!!!
The distribution of a variable describes what values the variable takes and how often it takes them. **CAUTION!!!! pg 3
Not every variable that takes number values is quantitative!!
Zip Codes - Can you talk about the average zip code? PROBLEM:
(a) Who are the individuals in this data set?
(b) What variables were measured? Identify each as categorical or quantitative. In what units were the quantitative variables measured?
(c) Describe the individual in the highlighted row. Two-Way Tables - 2 Categorical Variables
Ex: pg 12 Marginal Distribution
Ex: pg 13 Conditional Distribution
Ex: pg 15 Organizing a Statistical Problem Four-Step Approach - pg 18
Ex: Women's and Men's Opinions Association
Does not mean CAUSATION! DATA EXPLORATION A Titanic disaster
In 1912 the luxury liner Titanic, on its first voyage across the Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. The two-way table below gives information about adult passengers who lived and who died, by class of travel. The movie Titanic, starring Leonardo DiCaprio and Kate Winslet, suggested the following:
•First-class passengers received special treatment in boarding the lifeboats, while some other passengers were prevented from doing so (especially third-class passengers).
•Women and children boarded the lifeboats first, followed by the men. 1.What do the data tell us about these two suggestions? Give appropriate graphical and numerical evidence to support your answer.
2.How does gender affect the relationship between class of travel and survival status? Explain. Simpson's Paradox
Ex: pg 20 - Lurking.... Reversing an Association???!!!?? How to Explore Data
Explore data, don't just write down the first thing you see......You are on a TREASURE HUNT for interesting information! From Data Analysis to Inference * Data is everywhere, there is just too MUCH of it!
*6,500 Walmart stores in 15 different countries = TONS of data recorded every SECOND!
*We need to hear what the data are saying! ***Individuals DO NOT have to be people, they could be trees, M&M's, any object! AP EXAM TIP!!!! pg 3 **Not as important in AP, but worth knowing, we will cover this more in later Chapters. :-) What VALUES a variable takes, and how often it takes them. Drawing conclusions that go beyond the data. Moving from Descriptive (describing with numbers), to Hypothesizing about a Population! The values of a categorical variable are the labels for the categories: Male/Female.
Ex: pg 8 Radio Stations - Frequency table/ Rel. Freq table -- Counts and Percents
-Roundoff Error AP prefers bar graphs to pie, but pie charts are EVERYWHERE in the media. Bar graphs are easier to interpret and compare!!
AP COMMON ERROR!!! - DON'T FORGET LABELS/SCALE!!!!! They ALWAYS cause a deduction in your score, so LABEL, LABEL, LABEL!!!!!!!! Ex: pg 10 and 11 - Regular Stats Info - know how to make a GREAT Graph! Make sure to notice scales!!!! Misleading Graphs will COST YOU! *Look at the distribution of each variable separately.
*Think about HOW OFTEN this outcome occurs.
*If Row and Column totals are missing, CALCULATE THEM! Percents are more informative than counts, what means more to you, 7/10 or 70%? Hint - Conditional satisfies a CONDITION, a requirement that needs to be met FIRST - Out of those being female, how many said almost no chance? (96/2367) 2367 is the total # of Females, and is the condition. MINITAB!!!!! pg 16 CAUTION!! Even a strong association can be influenced by other variables "lurking" in the background - more on this later! :-)