Week 3 Statistics (Math 221) Slides

1. B. Heard
(These may not be copied, reproduced, or posted
in an online classroom without my permission.
Students may download one copy for personal use.)

2.  Data Collection
 Understand and distinguish between
 Sampling
 Census
 Experiments
 Simulations
 Etc.

3.  Descriptive & Inferential Statistics
 Know the difference
 Descriptive - This is a set of methods to describe
data that we have collected.
 Inferential - This is a set of methods used to
make a generalization, estimate, prediction or
decision.

4.  Knowthe difference between Qualitative and
Quantitative Data

5.  Types of Sampling
 Random
 Stratified
 Cluster
 Systematic
 Convenience

6.  Populations and Samples
 Parameters and Statistics

7.  Standard Deviation and Variance
 How to calculate and mathematical relationship.
 Variance is the Standard Deviation squared.
 Standard Deviation is the square root of the
Variance.
 For example if you are given the standard
deviation is “3” and asked what the variance
is, you would note it as “9” because 3^2 is 9.
 If you were given the variance as 4.7 and asked
for the standard deviation, you would note it as
“2.17” because √4.7 = 2.17

8.  Be able to get a regression equation.
 Example
 Data (4, 30), (4,35), (5,36), (6,42), (8,48)

9.  Be able to get a regression equation.
 Example
 Data (4, 30), (4,35), (5,36), (6,42), (8,48)

10.  Be able to get a regression equation.
 Example
 Data (4, 30), (4,35), (5,36), (6,42), (8,48)

11.  Be able to get a regression equation.
 Example
 Data (4, 30), (4,35), (5,36), (6,42), (8,48)
This would be written
as y = 3.982x + 16.70

12.  Use a multiple regression equation.
• “Plug and Chug” (Plug in the values and chug out
the answer)
• Example
y = -6.5 +12a + 5.1b where “a” is a vocabulary
score and “b” is a skills test score. y predicts
the person’s score on a job performance test.
Predict a job test score for a person who made a
50 as a vocabulary score and got a 7 as a skills
test .
y = -6.5 +12(50) + 5.1 (7)
y = 629.2

13.  Correlation Coefficients, also noted as “r”
• Range from -1 to +1
• .75 to 1 is strong
• .5 to .75 is moderate
• .25 to .5 is weak
• 0 to .25 is almost none, I would probably note it
is as “NO CORRELATION”
• + would be positive correlation, - would be
negative correlation
• For example, -0.58 would be moderate negative
correlation

14. From Page 487 in our text

15.  Be able to create a stem and leaf plot
 Use Minitab!
 Determine descriptive statistics.
• Mean, Median, Mode, Range, Variance, Standard
Deviation
 Use Minitab!

16.  Identify Class Width
 Identify Midpoint of certain classes
 Identify class boundaries
 Give the relative frequency
 Fishing Tournament Data below is an example
Number of Fish Frequency
0-7 9
8-15 15
16-23 12
24-31 3

17.  Class Width is 8
Number of Fish Frequency
0-7 9
8-15 15
16-23 12
24-31 3
8-0 = 8, or you could have
said 15 – 7 = 8, or count
on your fingers,
0,1,2,3,4,5,6,7
(There are eight numbers,
don’t let it fool you)

18.  Midpoint of second class is 11.5
Number of Fish Frequency
0-7 9
8+15 = 23
divided by 2 8-15 15
gives you 11.5 16-23 12
24-31 3

19.  What are the class boundaries of the third class?
15.5 and 23.5
Number of Fish Frequency
0-7 9
8-15 15
Subtract .5 from 16-23 12
the lower to get 24-31 3
15.5 and add .5
to the upper to
get 23.5

20.  Give the relative frequency of all classes
Number of Fish Frequency Relative Frequency
0-7 9 9/39
8-15 15 15/39
16-23 12 12/39
24-31 3 3/39
Total of 39
Total your Frequency column, the total is your
denominator for your fractional relative frequencies.
You could also have noted these in decimal form.

21.  Come see me at the “Statcave”
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 I often post helpful things there for fun and
you can look at old posts that may be
helpful.