LECTURE 2 Flashcards
What is quantitative research?
Research that explains phenomena using numerical data analyzed statistically.
What is qualitative research?
Exploratory research to understand reasons and motivations using methods like interviews and focus groups.
Why do we use samples in research?
It is impractical to test entire populations; samples represent populations.
What is a representative sample?
A sample that matches the general characteristics of the population.
What are descriptive statistics?
Statistics that describe the data in a sample.
What are inferential statistics?
Statistics that use sample data to make inferences about a population.
What is a within-subjects design?
All participants receive every treatment or condition.
What is a between-subjects design?
Participants are divided into groups, each receiving different treatments or tasks.
What is an independent variable (IV)?
A variable controlled by the researcher to observe its effect on the dependent variable.
What is a dependent variable (DV)?
The outcome measured, which depends on the independent variable.
What are nominal variables?
Categorical data without a meaningful order (e.g., smoker/non-smoker).
What are ordinal variables?
Ordered data without consistent intervals (e.g., race positions, Likert scales).
What are interval variables?
Data with consistent intervals but no true zero (e.g., temperature).
What are ratio variables?
Data with consistent intervals and a true zero (e.g., height, weight).
What is the mode?
The most common value in a dataset.
When is the mode useful?
For nominal data.
What is the median?
The middle value when data is ordered.
When is the median useful?
For ordinal data or skewed distributions.
What is the mean?
The arithmetic average of a dataset.
When is the mean appropriate?
For normally distributed interval or ratio data.
What are the weaknesses of the mode?
It ignores other data points and focuses on just one value.
What are the weaknesses of the median?
It uses only 1-2 central data points.
What are the weaknesses of the mean?
It is sensitive to extreme values and not suitable for categorical data.
What is a normal distribution?
A symmetric, bell-shaped distribution where mean, median, and mode are close together.
What is a skewed distribution?
A distribution where most data is concentrated at one end, affecting the mean.
What is a trimmed mean?
A mean calculated after removing extreme values from both ends of the distribution.
What is the range?
The difference between the highest and lowest values in a dataset.
What are the weaknesses of the range?
It is sensitive to extreme values.
What is the interquartile range (IQR)?
The range of the middle 50% of data, calculated by removing the upper and lower 25%.
What is variance?
The average of the squared differences from the mean.
What is standard deviation (SD)?
The square root of variance, showing the spread of data around the mean.
How much data falls within ±1 SD in a normal distribution?
68%.
What is an example of normally distributed data?
IQ scores, where 68% of scores fall between 85 and 115.
What should always be reported together?
Measures of central tendency and measures of dispersion.
What are the two main types of quantitative data?
Descriptive and inferential statistics.
What do descriptive statistics do?
Summarize information about the sample.
What do inferential statistics do?
Allow generalizations about the population based on the sample.
