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PPD 404. Robert A. Stallings RGL 200 Hours: Wednesdays 2:00 – 4:00 p.m. e-mail: [email protected] Web page: www~rcf.usc.edu/rstallin.

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Ppd 404
PPD 404

Robert A. Stallings

RGL 200

Hours: Wednesdays 2:00 – 4:00 p.m.

e-mail: [email protected]

Web page: www~rcf.usc.edu/rstallin


Dates and exact weights of all required activities are as follows:Excel Exercise One Due September 20 2.5 percentFirst Examination September 25 20 percentSAS Exercise One Due October 16 10 percentSecond Examination November 8 25 percentExcel Exercise Two Due November 22 2.5 percentSAS Exercise Two Due December 6 10 percentFinal Examination December 13 30 percent


Introduction to statistical analysis
Introduction to Statistical Analysis follows:

Involves mathematically manipulating quantitativedata

Aim is to identify patterns that explain something about the “real world”

Possible explanations are stated as hypotheses


Hypotheses
Hypotheses follows:

Essentially “hunches” about how things are related in the “real world”

Statements linking two (or more) variables

If X exists, then Y is likely to exist also

Alternatively, Y = f(X)


Variables
Variables follows:

Properties of objects that differ as you move from object to object

• for example, people’s weight (in pounds)

110, 258, 160, 210, 175, 120, 300, 120, 193

• NOTE that to differ does NOT mean that two (or more) people cannot have the same weight

• If everyone had the same weight, then weight would be a constant rather than a variable


Variables continued
Variables follows: (continued)

Properties of objects that differ from one object to another can also be qualities rather than something that we measure (such as people’s weight)

For example, people’s gender (female or male) can also be treated as a variable

If everyone in a group of people were of the same gender, then gender would be a constant


Variables can be one of two types
Variables can be one of two types follows:

  • Discrete variables

    things that you can count and report frequencies

    e.g., the number of women in this room

  • Continuous variables

    things that you can measure and report values

    e.g., the ages of all students in the room


Sirkin pp 34 52 identifies four types of variables
Sirkin (pp. 34-52) identifies four types of variables: follows:

  • Nominal-level variables

    these are discrete variables

  • Ordinal-level variables

    a “mixed” type

  • Interval-level variables

    equal-interval scales

  • Ratio-level variables

    equal intervals AND meaningful zero point


Only two statistical tasks
Only follows:TWO Statistical Tasks

  • Description

    Central Tendency

    Variability

    Association

  • Inference

    Estimation

    Hypothesis Testing


A diagnostic exercise for review purposes
A Diagnostic Exercise follows:(for review purposes)


1 solve for y where a 2 b 6 c 3 and d 5
1. Solve for follows:Y where a = 2, b = 6, c = 3, and d = 5


Y 0 2857 y 0 286
Y follows: = 0.2857Y = 0.286


2 solve for y where n 74
2. Solve for follows:Y where n = 74


Solve for y where x 1 17 x 2 23 and x 3 31
Solve for follows:Y where X1 = 17, X2 = 23, and X3 = 31


Y 17 23 31 2 y 71 2 y 5 041 00
Y = follows:(17 + 23 + 31)2Y = (71)2Y = 5,041.00


4 solve for y where x 1 17 x 2 23 and x 3 31
4. Solve for follows:Y where X1 = 17, X2 = 23, and X3 = 31


Y 17 2 23 2 31 2 y 289 529 961 y 1 779 00
Y = follows:172 + 232 + 312Y = 289 + 529 + 961Y = 1,779.00


5 round to the nearest three decimal places 0 6154 1 8485 2 6735 0 0046
5. follows:Round to the nearest three decimal places 0.6154 = 1.8485 = 2.6735 = 0.0046 =


0 6154 0 615 1 8485 2 6735 0 0046
0.6154 = 0.615 follows: 1.8485 = 2.6735 = 0.0046 =


0 6154 0 615 1 8485 1 848 2 6735 0 0046
0.6154 = 0.615 follows: 1.8485 = 1.848 2.6735 = 0.0046 =


0 6154 0 615 1 8485 1 848 2 6735 2 674 0 0046
0.6154 = 0.615 follows: 1.8485 = 1.848 2.6735 = 2.674 0.0046 =


0 6154 0 615 1 8485 1 848 2 6735 2 674 0 0046 0 005
0.6154 = 0.615 follows: 1.8485 = 1.848 2.6735 = 2.674 0.0046 = 0.005


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