1.5: Statistical Analysis in Psychology

Question 1

Descriptive Statistics

Answer 1

Involves the use of numerical data to measure and describe the characteristics of groups, and this includes measures of central tendency and variation.

It does not involve making inferences about a population based on sample data.

Question 2

Inferential statistics

Answer 2

Involves using statistical methods to make inferences about a population based on data.

It allows you to draw conclusions about a population based on the characteristics of a sample.

Specifically, it provides a way to see validity drawn from the results of the experiment

Question 3

Differences Between Descriptive Statistics & Inferential Statistics

Answer 3

Descriptive statistics describe the data, while inferential statistics tell us what the data means.

Question 4

What Do You Use When You Summarizing Data?

Answer 4

Descriptive Statistics.

Question 5

Measures of Central Tendency

Answer 5

Measures of central tendency are statistical values that represent the center or typical value of a dataset.

The three most commonly used measures of central tendency are the mean, median, and mode.

Question 6

Mean

Answer 6

The average of a set of scores.

You can calculate the mean by summing all of the values in a dataset and dividing by the total number of values.

The mean is sensitive to outliers, or unusually large or small values, and can be affected by them.

Question 7

Median

Answer 7

The middle score of distribution, separating the higher half of the data from the lower half.

The median is not affected by outliers and can be a better measure of central tendency when the dataset contains outliers.

Question 8

Mode

Answer 8

The most frequently recurring score in a dataset.

A dataset can have one mode, more than one mode, or no mode. If two scores appear the most frequently, the distribution is bimodal. If three or more scores appear most frequently, the distribution is multimodal.

Question 9

Measures of Variation

Answer 9

Standard Deviation & Range

Question 10

Standard Deviation

Answer 10

The most commonly used measure of variation.

A measure of how much the values in a dataset deviate from the mean. It is basically used to assess how far the values are spread below and above the mean.

A dataset with a low standard deviation has values that are relatively close to the mean, while a dataset with a high standard deviation has values that are more spread out.

Question 11

Range

Answer 11

Range is just the difference between the highest and lowest values in the dataset.

Question 12

Correlation Coefficient

Answer 12

A statistical measure that describes the strength and direction of the relationship between two variables.
It can range from -1 to 1.

A value of -1 indicates a strong negative relationship, a value of 1 indicates a strong positive relationship, and a value of 0 indicates no relationship.

Question 13

Positive Correlation

Answer 13

Shows that as one variable increases, the other variable increases.

For example, a positively correlated group may show that as height increases, weight increases as well.

Question 14

Negative Correlation

Answer 14

Shows that as one variable increases, the other decreases.

An example of a negative correlation could be how as the number of hours of sleep increases, tiredness decreases.

Question 15

No Correlation

Answer 15

No correlation shows that there is no connection between the two variables.

An example of no correlation could be IQ and how many pairs of pants an individual owns.

Question 16

Frequency Distribution

Answer 16

A breakdown of how the scores fall into different categories or ranges.

Question 17

Types of Frequency Distributions

Answer 17

Normal Distribution, Bimodal Distribution, Positively-Skewed Distribution, & Negatively-Skewed Distribution.

Question 18

Normal Distribution

Answer 18

A bell-shaped frequency distribution that is symmetrical about the mean.

Question 19

Bimodal Distribution

Answer 19

A frequency distribution with two peaks.

This occurs when the dataset has two distinct groups of values that occur with different frequencies.

Question 20

Positively-Skewed Distribution

Answer 20

A tail extending to the right (towards larger values).

This occurs when the dataset has a few unusually large values that pull the mean to the right.

Question 21

Negatively-Skewed Distribution

Answer 21

A tail extending to the left (towards smaller values).

This occurs when the dataset has a few unusually small values that pull the mean to the left.

Question 22

Normal Curve

Answer 22

Two important values that you should memorize: 68% and 95%.

This is a normal curve that includes data about intelligence.

Basically, 68% of the data falls within one standard deviation of the mean. Here, one standard deviation is equivalent to 15, so the data falls between 85 and 115, or +- 15 points of 100.

95% of the data falls within two standard deviations of the mean. Since 2 standard deviations are equal to 30, the data falls between 70 and 130, or +-30 points of 100.

Question 23

Statistical Significance

Answer 23

The likelihood that something occurs by chance.

If something is statistically significance, it did not occur by chance (some outside factor influenced the data).

If something isn’t statistically significant, it occurred completely by chance. To determine this, you would compare the mean of the control group and the mean of the experimental group.