AD RESEARCH FINAL: Descriptive Statistics

Variable B has to change at the same time as Variable A

Correlation

"R" value Indicates the strength of a linear relationship

Correlation Co-efficient

- Study a group of data and inferring the sample projects onto the larger population - More powerful than descriptive - Process of statistical inference

Inferential Statistics

Used to make estimates of how likely it is these statistics represent the population

Inferential Statistics

Simplest technique for analyzing nominal variables in bivariate ways

Cross Tabulation

Technique for studying the relationships between variables

Cross Tabulation

simple, but important technique for studying the relationship between variables. (Percentaging a Table- Rule for Percentage Calculations: Always calculate percentages in the direction of the causal factor (antecedent) and across the effect (criterion) factor).

Cross Tabulation

Bell-shaped - Positive Skew - Negative Skew -

Curves and their shapes

- Used with interval and ratio - Average - Most powerful

Mean

- Dispersion measures describe the way in which the scores are spread out about a central point. - The range is the difference between the highest and lowest scores in a distribution of scores. - Variance provides a mathematical index of the degree to which scores deviate from, or are at variance with, the mean.

Measures of Dispersion

Describe the way in which the scores are spread out about a central point

Measures of Dispersion

- Midpoint of distribution - Used with interval and ratio

Median

The main purpose for summary and descriptive methods of quantitative analysis are to reduce data and to enable us to see patterns and trends. You run the stats. If you find something important, you highlight it in the report. You always start with univariate statistics and analyses. Then you move on to whatever bivariate analyses will reveal something important about the research problem.

Methods

- Used only with nominal level of measurement (weakest)

Mode

Means that 1 set of variables increases while the other set or sets decreases

Negatie Correlation

Tool that enables us to make inferences from samples to populations

Normal Curve

- Has a sign indicating direction of relationship - Number indicates strength of relationship - Meaningful value when squared

Pearson's Product Moment Correlation

When 2 or more sets of variables gain in value together, not necessarily at the same time.

Positive Correlation

What kind of technique is a thematic apperception test?

Projective Technique

Data Distributions- (an unordered array of responses), Frequency Distributions- (a typical frequency distribution table consist of two columns -the possible values of the variable in the form of categories and the number of occurrences, or frequency, of each value). "Collapsing" the Data- (condense the data)

Quantitative Analysis

What is the most common method for determining correlation

Regression Analysis

The probability in the area below a normal curve

Rejection of the null hypothesis

What has to be at least ordinal level for the median to be a meaningful measure of central tendency?

A distribution of numbers

Where does the independent variable go in a contingency table?

At the top of a cross tabulation of contingency table

Numerical expressions of the degree to which two variables change in relation with one another (covary) are called measures of association or correlation. Typically, the variable presumed to be antecedent is designated "X" and the criterion "Y".

Basic Correlation Statistics

- Normal distribution of scores - Cluster around the mean

Bell-Shaped Curve

"What can we do with that data using bivariate analyses that help us address the original research problem at greater depth?"

Bivariate

use a scatterplot

Bivariate

Provides assurance that any random sample statistic comes from a population of statistics that form a normal curve around the true population parameter.

Central Limit Theorem

- Values identified by "x" - Used to measure data at a nominal level - Used to test distribution frequency to single-variable or to compare groups

Chi-Square

Examples of Bivariate Statistics?

Chi-Square Correlation ANOVA

The level of statistical confidence that is built into the sample

Confidence Level

Means that two or more sets of variables are related to one another at the interval or rational level

Correlation

What is another form of determining correlation?

Significance

The process of estimating parameters from statistics we always study samples instead of populations

Statistical Inference

The arithmetic average. The most power, but comes at a price.

The Mean

The midpoint of a distribution

The Median

The score or scores occurring most frequently

The Mode

All projective techniques share what element in common?

They are all based on the projective hypothesis

The square root of the variance of a distribution of numbers is the standard deviation

True

True or False? A distribution of numbers has to be at lease ordinal level for the median to be a meaningful measure of central tendency?

True

True or False? A distribution of numbers has to be at least ordinal level for the median to be a meaningful measure of central tendency

True

True or False? All quantitative data, regardless of level of measurement, can be analyzed with frequency distribution tables, proportions, percentages and ratios

True

True or False? Frequency distributions are one method for presenting data in descriptive statistical analysis

True

True or False? If there is an even number of scores or observations in a distribution, you use the mean of the two middle scores to calculate the median.

True

True or False? If you want to know how well the mean represents a distribution of numbers, you should also look at the standard deviation

True

True or False? Inferential statistics are more powerful than descriptive statistics.

True

True or False? Measure of dispersion can be used to reveal the "shape" of a distribution of scores or numbers

True

True or False? Measure of dispersion could be used to reveal the shape of a distribution of scores or numbers.

True

True or False? The chi-square statistic and test for significance is typically used with data measured at the nominal level.

True

True or False? The mean is sensitive to extreme values and should be supplemented with another measure of central tendency when there are extreme values in a distribution.

True

True or False? The term that's used to describe whether a distribution's curve is tall and peaked or short and flat is called "kurtosis"

True

True or False? Unlike the mode and the median, the mean takes into account all the values in a distribution making it especially sensitive to the effects of extreme scores

True

True or False? You could reduce data using a frequency distribution table.

True

Once you've collected your data, you begin with univariate analysis. One good way to begin is by looking at the items you have that measure related concepts and variables.

Univariate

Measures of central tendency and dispersion are examples of what?

Univariate Statistics

- Single variable - Simplest form of data tabulation - Involves the presence of frequency and distribution

Univariate Variable

Probability level is usually expressed by a lowercase _____?

p (in italics) followed by a less that or equal to sign and a value

The sum of all scores in a distribution of numbers, divided by the number of scores is the definition of _____

the mean

What are examples of bivariate statistics?

- Chi Square - Correlation - ANOVA

What are examples of univariate statistics?

- Measures of central tendency - Dispersion

The different measures of dispersion

- Range - Variance - Standard deviation

Quantitative Analysis

- Starts with little background info - Objective - Deductive and logical - Provides generalizations - Sample size is essential - Goal is to classify and count - Uses measuring instruments

What are some data tabulation issues?

- hand tabulation is inefficient - human error while recoding - lose sight of micro-level trends - average of data does not show the entire picture - collapsing data lessens precision of analysis

o Hand Tabulation: unless your data set is especially small, hand tabulation is likely to be inefficient and time prohibitive. If you have a simple questionnaire, and you are looking for a very specific set of data, then hand tabulation may be efficient. o Computer Tabulation: It is convention for each row to represent a unit of analysis and each column to represent a variable. Data are entered as close to the raw form as possible. Computer programs can recode variables without error while human error is almost assured in recoding large data sets. o The Single Variable: The simplest form of data tabulation involves a single variable and is often called univariate, meaning one variable. At the most basic level, it is helpful to know how many times each option was chosen for the variable. How many were male or female? How many people strongly agreed or disagreed with the statement. o Getting A Good Look At The Data: There is no one way to tabulate data. No matter how data are tabulated, there will be some consolidation and lack of clarity. As you step back, you can begin to see patterns in the data; however; you also will begin to lose sight of micro-level trends in the data. In this sense, data tabulation is about the processing of coming to understand your data rather than simply going through a checklist.

Data Tabulation and Findings Presentation Issues

A variable that goes down the side of a cross tabulation table and whose values are in the rows should be the

Dependent Variable

- Range - the difference between the highest and lowest scores in a distribution of scores - Variance - provides a mathematical index of the degree to which scores deviate from, or are at variance with, the mean. - Standard Deviation - overcomes the problem of variance not being calibrated in the same units as the original data by taking the square root of the variance.

Dispersion

True or False? A cross tabulation is used when one nominal-level variable and one interval-level variable need to be analyzed simultaneously to see if there's a relationship between them

False

True or False? A cross-tabulation is used when one nominal-level variable and one interval-level variable need to be analyzed simultaneously to see if there's a relationship between them

False

True or False? If you wanted to test more than two mean scores you'd have to use a t-test instead of ANOVA

False

True or False? It is generally assumed that 100% of the scores in a distribution of numbers will fall within plus or minus two standard deviations from the mean, especially if the distribution is believed to be normal

False

True or False? It is generally assumed that 100% of the scores in a distribution of numbers will fall within plus or minus two standard deviations from the mean, especially if the distribution is believed to be normal.

False

True or False? Measures of central tendency and dispersion are examples of bivariate statistics.

False

True or False? Measures of central tendency and dispersion are examples of bivariate statistics?

False

True or False? The Median and Mean can be used to analyze all four levels of measurement

False

True or False? When testing for Mr. Pearson's r for statistical significance, the null hypothesis is almost always that the correlation between the two variables in the population is greater than .05

False

What is the most important feature of a normal curve?

Fixed areas below the normal curve represent the frequency of the scores of values of a variable that fall in those areas. Allows us to know how variables vary without measurement

Are summary descriptive statistics a way to reduce data?

Yes. - Measures of Central Tendency - Mean, Median, Mode