PARAMETRIC Pt.3 Flashcards

1
Q
  • Determines whether there exists a relationship between variables
A

Correlation

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2
Q

movement together
- ρ(x,y) = ρ(y,x)

A

Correlation

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3
Q

Describe the nature of the relationship between variables.

A

Regression

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4
Q
  • one variable affects the other
  • cause and effect
  • one way
A

Regression

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5
Q

2 TYPES OF RELATIONSHIPS

A

Simple Relationship
Multiple Relationship

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6
Q

1 independent (explanatory/predictor) and 1 dependent (response) variable
- can also be positive (directly proportional) and negative (inversely proportional)

A

Simple Relationship

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7
Q
  • multiple regression
  • > 2 independent variables are used to predict 1 dependent variable
A

Multiple Relationship

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8
Q

This ___________ means that there is no correlation between the x and y variables in the population.

A

null hypothesis

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9
Q

This _________________ means that there is a significant correlation between the variables in the population.

A

alternative hypothesis

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10
Q

PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT

A

SCATTER PLOTS

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11
Q
  • determines the strength of the linear relationship between two variables.
A

Correlation Coefficient

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12
Q

2 types of Correlation Coefficient

A

population & linear

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13
Q
  • denoted by the Greek letter ρ is the correlation computed by using all possible pairs of data values (x, y) taken from a population.
A

Population correlation coefficient

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14
Q

Population correlation coefficient is denoted by

A

ρ

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15
Q

measures the strength and direction of a linear relationship between two quantitative variables.

A

Linear correlation coefficient

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16
Q

The symbol for the sample correlation
coefficient is

A

r

17
Q

Linear correlation coefficient is also called

A

Pearson product moment correlation coefficient (PPMC)

18
Q

Pearson product moment correlation coefficient (PPMC) is also known as

A

Linear correlation coefficient

19
Q

Range of the linear correlation coefficient is from

A

-1 to +1

20
Q

the value of r will be close to +1.

A

Strong positive linear relationship

21
Q

the value of r will be close to -1.

A

Strong negative linear relationship

22
Q

weak realtionship

A

No linear relationship

23
Q

the value of r will be close to 0.

A

No linear relationship

24
Q

implies only that there is _______________ between the variables

A

No linear relationship

25
Q

x causes y | There is a _______ cause-and-effect relationship between the variables.

A

direct

26
Q

y causes x | There is a _________ cause-and-effect relationship
between the variables.

A

reverse

27
Q

When the null hypothesis has been rejected for a specific α value, any of the following five possibilities can exist.

A
  1. There is a direct cause-and-effect relationship between the variables.
  2. There is a reverse cause-and-effect relationship between the variables.
  3. The relationship between the variables may be caused by a third variable.
  4. There may be a complexity of interrelationships among many variables.
  5. The relationship may be coincidental.
28
Q
  • The sample must be randomly selected from the population
  • The population must be normally distributed for the variable under study
  • The observations must be independent of one another
A

CHI-SQUARE DISTRIBUTION (1 VARIANCE)