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STAT 110 - Section 5 Lecture 12. Professor Hao Wang University of South Carolina Spring 2012. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A. Roadmap. Statistics deals with data. We know how to get good data. - random sampling
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STAT 110 - Section 5 Lecture 12 Professor Hao Wang University of South Carolina Spring 2012 TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAA
Roadmap • Statistics deals with data. • We know how to get good data. • - random sampling • - randomized comparative experiments • So, what’s the best way to present data?
Data Tables Eye Color of 46 Students Eye Color # of persons percent Brown 18 39% Blue 17 37% Green 6 13% Hazel 4 9% Other 1 2% Total 46 100%
Data Tables • What makes a good data table? • - labels • - units • - source • Tables typically summarize data. • But do they tell the whole story?
Types of Variables categorical variable – places an individual into one of several groups or categories Example: Gender, college attended, field of study quantitative variable – takes numerical values for which arithmetic operations make sense operations: adding, averaging, etc. Example: Height, income, GPA, stock price, length
Eye Color of 46 Students Eye Color # of persons percent Brown 18 39% Blue 17 37% Green 6 13% Hazel 4 9% Other 1 2% Total 46 100% What kind of variable is eye color? A – Categorical B - Quantitative
Eye Color of 46 Students Eye Color # of persons percent 1 18 39% 2 17 37% 3 6 13% 4 4 9% 5 1 2% Total 46 100% What kind of variable is eye color? A – Categorical B - Quantitative
Definitions frequency – the number of times a value occurs in the data relative frequency – for a value, the proportion (fraction or percent) of all observations that have that value
Eye Color of 46 Students Eye Color # of persons percent Brown 18 39% Blue 17 37% Green 6 13% Hazel 4 9% Other 1 2% Total 46 100% Which column is the frequency? A – Eye Color B - # persons C - percent
Pie Charts Pie Chart of the Eye Color Data
Pie Charts • shows how a whole is divided into parts • How do you make a pie chart? • (1) draw a circle - this represents the whole • (2) draw wedges in proportion to the size of each part - each wedge represents each part • angles are harder to compare than lengths. • not a good way to compare sizes of the parts
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Bar Graphs • height of each bar shows rate or count • easier to draw than a pie chart • Called a “Frequency Bar Graph” when counts are used • Called a “Relative Frequency Bar Graph” when percentages are used
Which of the values can not be used on the vertical axis of a Relative Frequency Bar Chart? • A. 0 • B. 0.25 • C. 50% • D. 150
Pictogram • Typically more interesting than a bar graph because it uses pictures in place of the bars.
Be careful about pictogram Plus: Can be more visually appealing than a bar graph Minus: Can be misleading because our eyes respond to total area, not just height
Line Graph: Average Price for Regular Unleaded Gasoline (Bureau of Labor Statistics)
Line Graph • To display change over time, make a line graph. This can be used to display a quantitative variable changing over time. A line graph of a variable plots each observation against the time at which it was measured. • Time always goes on the horizontal scale. • Variable you’re measuring always goes on the vertical scale. • Connect the data points by lines to display the change over time.
Average Unemployment Rate Blue = High School GradsPink = College Grads
What should we look for? • Overall pattern. • A trend is a long-term upward or downward movement over time. • Striking deviations. • Seasonal variation. • A pattern that repeats itself at known regular intervals of time is called seasonal variation. • Many series of regular measurements over time are seasonally adjusted.
Making Good Graphs • Use good labels and legends. • - variables, units, source • Make the data stand out! • - Drawing a graph isn’t a creative art project. • Pay attention to what the eye sees. • - Avoid pictograms and fancy 3D effects. • Watch the scales.