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”
 www.facebook.com/statcave
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 IT IS NOT REQUIRED TO BE ON FACEBOOK.
IT’S SOMETHING I DO FOR FUN.
 I post charts there because it is easy for me
to do.