PSYCHSTATS PRELIMS

Authority

One accepts the information as true because someone who is supposed to know tells you something is true.

Rationalism

This method uses reason alone to arrive at knowledge. One analyzes a situation and draws logical conclusions based on the information at hand.  The conclusion is not tested empirically to determine if it is correct.

Intuition

This is a sudden insight that springs into consciousness all at once as a whole.

Scientific Method

1. This method uses reasoning and intuition as a means of formulating an idea of what is true. Still, it then relies on objective assessment to verify or deny the validity of the idea.

• Creating Hypothesis

• Scientific Experiment

• Objective Assessment

• Forming Conclusion

The Scientific Methods are?

Observational Studies

In this research there is no direct experimental manipulation of variables, thus observational studies cannot determine causality.

• Naturalistic Observation

• Parameter Estimation

• Correlational Studies

Types of Observational Studies

Naturalistic Observation

To obtain accurate description of the situation being studied. Much anthropological, and etiological research is of this type.

Parameter Estimation

This is when an investigator tries to determine the actual characteristics of the population, based on measuring a subset of the population.

Correlational Studies

A type of observation where the relationship between the variables is studied.

True Experiments

The investigator attempts to determine if changes in one variable produce changes in another. only true experiments can determine causality.

Statistical Analysis

In both observational studies and true experiments, __________ is usually employed.

Descriptive Statistics

Analysis is conducted to describe the obtained data.

Inferential Statistics

Analysis is conducted to make inferences about a population using data obtained from the sample.

• Population

• Parameter

• Sample

• Statistic

• Variable

• Independent variable

• Dependent Variable

• Data

Research Variables?

Nominal

• The ________ scale is the lowest level of measurement. It is more qualitative than quantitative.

• ________ scales are comprised of elements that have been classified as belonging to a certain category.

• Nominal

• Interval

• Ordinal

• Ratio

Measurement Scales?

Ordinal

• possess a relatively low level of the property of magnitude.

• The rank order of people according to height is an example of a/an _______ scale.

• One does not know how much taller the first rank person is over the second rank person. Can determine whether A > B, A = B or A < B.

Interval

• This scale possesses equal intervals, magnitude, but no absolute zero point.

• An example Is temperature measured in degrees Celsius. What is called zero Is actually the freezing point of water, not absolute zero.

• Can do same determinations as ordinal scale, plus can determine if A - B = C - D, A - B > C - D, or A - B < C- D.

Ratio

• These scales have the most useful characteristics since they possess attributes of magnitude, equal intervals, and an absolute zero point. All mathematical operations can be pertormed on ratio scales.

• Examples include height measured in centimeters, reaction time measured in milliseconds.

Continuous Variables

• This varibale can be identified by the fact that they can theoretically take on an infinite number of values between adjacent units on the scale.

• Examples include length, time and weight. For example, there are an intinite number of possible values between 1.0 and 1.1 centimeters.

Continuous Variables

All measurements on a __________ variable are approximate. They are limited by the accuracy of the measurement instrument. When a measurement is taken, one is actually specifying a range of values and calling it a specific value.

Discrete Variables

• In this case there are no possible values between adjacent units on the measuring scale.

• For example, the number of people in a room has to be measured in discrete units. One cannot reasonably have 6 1/2 people in a room.

Frequency Distribution

A list of rank ordered scores and their frequency of occurrence in tabular form is called a __________. When the data is rank ordered, it is easier to understand.

Grouped Frequency Distribution

Individual scores are often grouped together into class intervals of equal width to allow one to visualize the shape of a distribution and its central tendency.

Relative Frequency Distribution

This indicates the proportion of the total number of scores that occurred in each interval.

Cumulative Frequency Distribution

• This indicates the number of scores which fell below the upper real limit of each interval.

• The _________ for each interval is found by adding the frequency of that interval to the frequencies of all the class intervals below it.

Cumulative Percentage Distribution

This indicates the percentage of scores which fell below the upper real limit of each interval.

Cumulative Percentage Distribution

This indicates the percentage of scores which fell below the upper real limit of each interval.

Bar Graphs

• are generally used for nominal or ordinal data.

• The abscissa shows categories and the ordinate frequency.

Histograms

• Are generally used for interval or ratio data.

• The abscissa shows the class interval for the data and the ordinate shows frequency. Vertical bars must touch each other.

Frequency Polygons

Similar to histograms, except that instead of using bars, a point is plotted over the midpoint of each interval at a height corresponding to the frequency of the interval.

Cumulative Frequency Polygons

• Shows the percentage of scores that fall below the upper real limit of the interval on the ordinate.

• The abscissa plots the upper limit of each class interval.

Symmetrical

Symmetrical distributions are those which when folded in half have the two sides of the curve correspond perfectly.

• Positively Skewed

• Negatively Skewed

Types of Skewed Distribution

Skewed

If a curve is not symmetrical, it is ______.

Positively Skewed

Skewed Right

Negatively Skewed

Skewed Left

Positively Skewed

Positive skew refers to curves where most of the scores occur at the lower values of the abscissa and tails off to the higher end.

Negatively Skewed

Negative skew refers to curves where most of the scores occur at the higher values and the curve tails toward the lower end of the abscissa.

Miscellaneous Shapes

Curves are sometimes described in terms of their shape. Examples include U-shaped distributions, J-shaped distributions, and rectangular.

Pearson’s R

• Measures the strength and direction of the linear relationship between two continuous variables.

Pearson’s R

Range: −1 to 1
1   = perfect positive correlation
0   = no correlation
−1 = perfect negative correlation

Range of Pearson’s R?

Range: −1 to 1
1   = perfect positive correlation
0   = no correlation
−1 = perfect negative correlation

Spearman’s Rho

Measures the strength of a monotonic relationship (increasing or decreasing) between two ordinal or continuous variables.

Spearman’s Rho

• Range : -1 to 1

• Useful for non-linear relationships

Spearman’s Rho

Rank Correlation

Spearman’s Rho

Checking the correlation between students’ ranks in math and physics exams.

Pearson’s R

Suppose we have height (in cm) and weight (in kg) data for a group of people.

Phi Coefficient

Measures the correlation between two binary (dichotomous) variables.

Phi Coefficient

Useful for analyzing 2×2 contingency tables.

Phi Coefficient

Determining correlation between gender (Male/Female) and preference for a product (Yes/No).

Tetrachoric Correlation

Estimates correlation between two dichotomous variables assumed to be normally distributed.

Tetrachoric Correlation

Only applicable to artificially dichotomized variables.

Tetrachoric Correlation

Converting continuous height (tall/short) and weight (heavy/light) into binary variables and estimating correlation.

Cramer

Measures association between two categorical variables.

Cramer’s V

Range : 0 (no association) to 1 (strong Association)

Cramer’s V

Checking association between different movie genres and favorite actors.

Theta Coefficient

Measures association between two categorical variables like Cramer’s V but is less common.

Goodman-Kruskal’s Gamma Coefficient

Measures the strength of association between ordinal variables. (Ordinal with many ties)

Goodman-Kruskal’s Gamma Coefficient

Range: −1 (strong negative association) to 1 (strong positive association).

Goodman-Kruskal’s Gamma Coefficient

Analyzing relationship between education level and job satisfaction.

Somers’ D (Polychoric Correlation - K Sample)

Measures ordinal association similar to Gamma but accounts for tied ranks.

Somers’ D (Polychoric Correlation - K Sample)

Comparing rankings of candidates by multiple judges.

Point-Biserial Correlation

Measures association between one binary variable and one continuous variable.

Point-Biserial Correlation

Relationship between gender (binary) and test scores (continuous).

Biserial Correlation

\Similar to Point-Biserial Correlation, but assumes the binary variable is artificially dichotomized.

Kendall’s Tau

Measures ordinal association between two variables, robust to ties.

Kendall’s Tau

Similar to Spearman’s Rho but less sensitive to outliers.

Kendall’s Tau

Ranking candidates by two different interviewers.