CHAPTER 4: STATISTICS REFRESHER 2

What are the FOUR TYPES/SHAPES of RELATIONSHIP?

Positive linear relationship

Negative linear relationship

Curvilinear relationship

No relationship

What type of statistics do we use if we want to draw conclusions about a SAMPLE and its corresponding POPULATION?

Inferential statistics

According to Cohen and Swerdik (2018), what is CENTRAL to PSYCHOLOGICAL testing and assessment?

Inferences about how traits, abilities, or interests relate to behavior

What are INFERENCES based on in research?

Data from a sample used to draw conclusions about a population

Which of the following is an example of a question that can be explored using CORRELATION?

Is my child's cellphone usage the reason for their declining grades?

Why is COMMON SENSE often INSUFFICIENT in determining relationships among VARIABLES?

Most of the time, common sense is not enough and reliable

What does the COEFFICIENT of correlation express?

The numerical index that expresses relationships between variables

When discussing the NATURE of correlation, what are we examining?

Two variables and tell us the extent to which X and Y are "co-related".

How is the meaning of the CORRELATION COEFFICIENT interpreted?

By its sign and magnitude

The VALUE of a CORELATION COEFFICIENT ranges from?

0 to 1 or -1

What does the MAGNITUDE in a correlation coefficient represent?

The strength of the relationship

If the value of a correlation coefficient is 1.5, what can we conclude?

It is wrong because the maximum is 1

How can the RELATIONSHIP between TWO VARIABLES be visually presented?

Scatter plot

What does a SCATTER PLOT provide regarding correlation?

The nature of correlation

What characterizes a POSITIVE LINEAR RELATIONSHIP?

Increases in the values of one variable are accompanied by increases in the values of the second variable (As the one variable increase the other variable increases)

Which of the following describes a NEGATIVE LINEAR CORRELATION?

Increases in the values of one variable are accompanied by decreases in the values of another variable

The social loafing phenomenon and the bystander effect are examples. Latane, Williams, and Harkins (1979) were intrigued with reports that INCREASING the number of people working on a task may actually REDUCED group effort and productivity. They ask participants to clap and as the size of the group increased, the amount of noise made by each individual decreased. This an example of:

Negative linear correlation

Example: want to know if "fast talkers" are more persuasive. In a study conducted by Smith and Shaffer (1991), students listened to a speech delivered at a show (144 words per minute), intermediate (162 wpm), or fast (214 wpm) speech rate. The speaker advocated a position favoring legislation to raise the legal drinking age; the students initially disagreed with this position

Postive linear correlation

What does a FLAT LINE on a graph indicate about the relationship between two variables?

There is no relationship between the two variables

Increases in the values of one
variable are accompanied by systematic increases and decreases in the values of the other variable. In other words, the direction of the relationship CHANGES at least ONCE. This type of relationship is sometimes referred to as a NON-MONOTONIC FUNCITON.

Curvilinear Relationship

Which of the following describes a NEGATIVE LINEAR EXAMPLE?

As stress levels decrease, the quality of sleep increases

When should the PEARSON R be used as a statistical tool?

when the two variables being correlated are continuous (or, they can theoretically take any value)

What TWO TYPES of INFORMATION does the PEARSON R provide about the relationship between variables?

Strength and direction of the relationship

Why do we use STATISTICAL TREATMENT in research?

To provide objective responses. However, we need to follow a rule

What happens if we violate the rules for using the PEARSON R?

It cannot provide the expected correlation

If the Pearson correlation coefficient (r) is 0.8, how would you describe its DIRECTION and STRENGTH?

Positive direction; strong strength

What is the range of the PEARSON CORRELATION COEFFICIENT (r)?

0.00 to +1.00 and 0.00 to - 1.00

What does a Pearson r correlation of 0.00 indicate about the two variables?

They are not related at all

If a Pearson correlation result is at 0.8, how would you describe the correlation in terms of MAGNITUDE and DIRECTION?

Strong and positive

Which value of Pearson r represents the STRONGEST POSSIBLE RELATIONSHIP?

+1.00 or -1.00

Which of the following values suggests a STRONG RELATIONSHIP in Pearson correlation coefficient (r)?

0.9

If the r-value is -0.5, what does this indicate about the strength and direction of the relationship?

Moderate strength and negative direction

A POSITIVE correlation coefficient suggests what kind of relationship?

High scores on one variable are associated with high scores on the other

Which of the following best describes a NEGATIVE linear relationship?

High scores on one variable are associated with low scores on the other

What is a LIMITATION of CORRELATION using Pearson r?

It cannot establish cause-and-effect relationships

If the P-VALUE is GREATER than < 0.05, what decision should be made about the null hypothesis?

retain the null hypothesis

The CORRELATION COEFFICIENT (r) represents a ratio between which two elements?

Covariance and separate variances

In a study with the null hypothesis "There is no significant relationship between neuroticism and job satisfaction," what would a P-VALUE LESS THAN 0.05 indicate?

The null hypothesis should be rejected

What does the COEFFICIENT OF DETERMINATION represent when interpreting the CORRELATION COEFFICIENT?

The amount of variance shared between two variables

For example, you correlate the number of hours spent on playing Mobile Legends ® online and the students' grades. You have computed a correlation coefficient of r= -0.40.

If the CORRELATION COEFFICIENT (r) between hours spent playing a game and grades is -0.40, what is the COEFFICIENT OF DETERMINATION?

16%

In a correlation study with r = -0.40, what percentage of the variance is UNIQUE and not shared between the two variables?

84%

If the UNIQUE VARIANCES are significantly GREATER than the SHARED VARIANCE, what will be true about the correlation coefficient (r)?

r will be low

If the SHARED VARIANCE between two variables is GREATER than the UNIQUE VARIANCE, what will be true about the correlation coefficient (r)?

r will be high

When should you NOT use PEARSON'S r?

When your data is nominal or ordinal

For PEARSON'S r to be valid, VARIABLES must be:

continuous (measured at interval or ratio level)

PEARSON'S r requires that the RELATIONSHIP between the two variables is:

linear

What will happen if there is NO LINEAR RELATIONSHIP between two variables?

Pearson's r cannot r cannot be used

One of the ASSUMPTIONS for using PEARSON’S r is that:

The variables are approximately normally distributed

One of the assumption in Pearson r is: There should be no significant outliers.

True

What is another name for SPEARMAN’S RHO?

Rank-order correlation coefficient

Spearman's rho is used when the DATA is ORDINAL or when:

Continuous data fails the assumptions for Pearson’s r

If a dataset DOES NOT MEET Pearson’s assumptions, what ALTERNATIVE correlation test can be used?

Spearman’s rho

Spearman’s rho works by TRANSFORMING the original SCORES into ___________ before performing further calculations. Look at the following data.

Nine people were asked to rate the attractiveness of a target person, and then rate themselves (myattract) on a 10-point scale from 1 (awful) to 10 (wonderful)

Ranks

Which STATISTICAL TEST measures the association between two CATEGORICAL VARIABLES?

Chi-square

Assumption #1 for using CHI-SQUARE is that your TWO VARIABLES should be MEASURED at:

Ordinal or nominal level

Assumption #2 for using 4 requires that your TWO VARIABLES should consist of TWO OR MORE:

Categorical, independent groups

Which of the following examples MEETS the CHI-SQUARE requirement of INDEPENDENT GROUPS?

Gender: male, female; Ethnicity: Caucasian, African American, Hispanic

Chi-square (X²) is used to measure the ASSOCIATION between TWO:

Categorical or nominal variables

If both the X-VARIABLE and Y-VARIABLE are CONTINUOUS, which correlation coefficient is appropriate?

Pearson r

When the Y-variable is CONTINUOUS and the X-variable is ARTIFICIAL DICHOTOMOUS, which correlation should be used?

Biserial r

If you have a TRUE DICHOTOMOUS variable and a CONTINUOUS VARIABLE, the correct correlation coefficient to use is:

Point-biserial r

A TRUE DICHOTOMOUS variable refers to a variable that has only TWO EXCLUSIVE AND EXHAUSTIVE CATEGORIES, such as:

Male and Female

The correlation used for ORDINAL DATA that does NOT meet the assumptions for Pearson’s correlation is:

Spearman rho

A TRUE DICHOTOMY involves variables that are:

Mutually exclusive and exhaustive

ARTIFICIAL DICHOTOMIES are those where:

Categories are based on an underlying continuum but assigned based on arbitrary criteria

REGRESSION is used to:

Predict values on one variable from another

Which type of regression is used when you want to predict a value using TWO OR MORE INDEPENDENT VARIABLES?

Multiple regression

In LINEAR REGRESSION, the VARIABLE we WANT to PREDICT is called the:

Dependent variable

Which variable is also known as the PREDICTOR VARIABLE in regression?

Independent variable

In a regression analysis where revision time PREDICTS EXAM PERFORMANCE, exam performance is the:

Dependent variable

If we use LINEAR REGRESSION to PREDICT SMOKING DURATION , based on CIGARETTE CONSUMPTION, which is the predictor variable?

Cigarette consumption

In regression, the INDEPENDENT VARIABLE is also known as the:

Predictor variable

The DEPENDENT VARIABLE in a regression analysis is also known as the:

Outcome variable

Which of the following is a CORRECT statement about REGRESSION?

Regression allows us to predict one variable from another

In regression analysis, the INDEPENDENT VARIABLE is the variable that:

We use to make predictions

LINEAR REGRESSION is used when we want to PREDICT the VALUE of a variable based on:

The value of another variable

The ____________ is found by using the principle of LEAST SQUARES, which MINIMIZES the SQUARED DEVIATION around the regression line.

Regression line

The REGRESSION LINE is found using which principle?

Least squares

If a score is EQUAL to the MEAN, its squared deviation is:

Zero

In the equation Y = a + b(x), a represents the:

Intercept

In the regression equation Y = a + b(x), the slope is represented by:

What is the PURPOSE of REGRESSION?

To find relationships

The point at which the REGRESSION LINE CROSSES the Y axis is called the: