Research Process and Statistical Analysis

These flashcards cover key concepts from the research process and statistical analysis as outlined in the lecture notes.

Research Process

A systematic approach to investigating a question, typically involving defining the problem, reviewing literature, formulating a hypothesis, selecting a research design, carrying out the research, analyzing data, and identifying key findings.

Hypothesis

A testable statement or prediction that addresses the research objectives.

Independent Variable

The variable that is manipulated or changed by the researcher to observe its effect on the dependent variable.

Dependent Variable

The variable that is measured in response to changes in the independent variable.

Observation vs Experimentation

Observation involves gathering data without manipulation of variables, while experimentation involves changing the independent variable to measure effects on the dependent variable.

Quantitative Data

Data expressed in numerical values that can be measured and analyzed statistically.

Qualitative Data

Data that is descriptive and conceptual, often presented in categories rather than numbers.

P-value

A statistical measure that indicates the probability that the observed variation is due to chance; a p-value less than 0.05 typically suggests statistical significance.

Null Hypothesis (H₀)

The hypothesis that there is no difference or effect; it is the default position that suggests any observed effect is due to chance.

Alternative Hypothesis (H₁)

The hypothesis that indicates the presence of an effect or a difference; it is what researchers aim to support through their findings.

Type 1 Error

Rejecting the null hypothesis when it is actually true, indicating a false positive.

Type 2 Error

Failing to reject the null hypothesis when it is actually false, indicating a false negative.

Statistical Power

The probability that a statistical test will correctly reject a false null hypothesis; power is influenced by sample size, effect size, and significance level.

Descriptive Statistics

Statistics that summarize or describe characteristics of a data set, typically including measures of central tendency and measures of dispersion.

Inferential Statistics

Statistics used to make inferences or generalizations about a population based on a sample of data.

Central Tendency

Measures that represent the center or typical value of a dataset, including mode, median, and mean.

Dispersion

Measures that describe the spread of data points in a dataset, including range, variance, and standard deviation.

Bias in Sample

The tendency for a sample to differ from a population, which can impact the validity of statistical conclusions.

Confounding Variable

A variable that influences both the independent and dependent variables and may lead to a false association.

Normal Distribution

A probability distribution that is symmetric about the mean, where most observations cluster around the center and probabilities for values farther from the mean taper off equally in both directions.