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What are the three basic components of statistical inference?

Point estimates, precision, and significance tests.

What is a confidence interval (CI)?

A range in which the true parameter is likely to lie, given the sample and a chosen confidence level.

What is the center of the sampling distribution equal to?

The population parameter P.

Which statistical test assesses whether a difference or relationship is real?

Significance tests or hypothesis tests.

What does a p-value represent in hypothesis testing?

The probability of observing results as extreme as or more extreme than those observed under the null hypothesis $H_0$.

What is multicollinearity?

When two or more independent variables in a regression model are highly correlated with each other.

What is the primary use of multiple regression in social research?

It predicts a dependent variable from several independent variables while controlling for others.

What are dummy variables used for in regression analysis?

To convert categorical variables into numeric indicators (0/1) for inclusion in regression.

What is the margin of error (MOE) formula for a 95% confidence interval?

MOE is approximately equal to 2 times the standard error (SE).

What is the main purpose of confidence intervals?

To provide a range in which the true population parameter is likely to lie.

What are the consequences of using a small sample size in significance tests?

Larger samples reduce standard error and increase the likelihood of detecting true effects; small samples may yield statistically insignificant results.

What is the significance level commonly used in hypothesis testing?

0.05 or 5%.

What is the concept of power in hypothesis testing?

The probability of correctly rejecting the null hypothesis when it is false.

What is the purpose of causal inference in social research?

To draw conclusions about cause-and-effect relationships between variables.

What do randomized controlled trials (RCTs) aim to achieve?

To test causal effects by manipulating an independent variable and observing changes in a dependent variable.

What is the role of prior probabilities in Bayesian inference?

Bayesian inference begins with prior probabilities that are updated with data to form posterior probabilities.

What do we mean by 'latent constructs'?

Latent constructs are traits that are not directly observable and are inferred from other measures.

Why is conceptualization important in measurement?

Conceptualization provides a clear definition of what is being measured, which is vital for operationalization.

How can a measure be reliable but not valid?

It consistently produces the same result but measures an incorrect or irrelevant construct.

What does a confidence interval typically indicate in research results?

A measure of the uncertainty surrounding a sample estimate, showing the range within which the true population parameter is expected to lie.

What is an example of a latent construct?

Intelligence or socioeconomic status.

What does it mean if a measure has high construct validity?

It effectively captures the intended concept and correlates as theoretically expected with other related measures.

What are the three basic components of statistical inference?

Point estimates, precision, and significance tests.

What does the standard error (SE) measure?

It measures the typical distance between a sample statistic and the population parameter due to sampling variability.

What is a confidence interval (CI)?

A range in which the true parameter is likely to lie, given the sample and a chosen confidence level.

What is the center of the sampling distribution equal to?

The population parameter P.

What does a p-value represent in hypothesis testing?

The probability of observing results as extreme as or more extreme than those observed under the null hypothesis $H_0$.

What is multicollinearity?

When two or more independent variables in a regression model are highly correlated with each other.

What are dummy variables used for in regression analysis?

To convert categorical variables into numeric indicators (0/1) for inclusion in regression.

What is the margin of error (MOE) formula for a 95% confidence interval?

MOE is approximately equal to 2 times the standard error (SE).

What is the main purpose of confidence intervals?

To provide a range in which the true population parameter is likely to lie.

What is the significance level commonly used in hypothesis testing?

0.05 or 5%.

How is practical significance different from statistical significance?

Practical significance refers to the real-world relevance of a finding, while statistical significance indicates the likelihood that a result is not due to chance.

What do randomized controlled trials (RCTs) aim to achieve?

To test causal effects by manipulating an independent variable and observing changes in a dependent variable.

What do we mean by 'latent constructs'?

Latent constructs are traits that are not directly observable and are inferred from other measures.

What is the difference between valid and reliable measures?

A valid measure accurately reflects the construct it intends to measure, while a reliable measure yields consistent results over time.

Why is conceptualization important in measurement?

Conceptualization provides a clear definition of what is being measured, which is vital for operationalization.

What is an example of systematic error in measurement?

Bias that consistently overestimates or underestimates the actual value, such as consistently miswriting a survey question.

What is an example of a latent construct?

Intelligence or socioeconomic status.

What is random sampling?

A sampling technique where every individual in the population has an equal chance of being selected for the sample, ensuring representativeness.

What is the primary difference between qualitative and quantitative research?

Qualitative research explores concepts through non-numerical data like interviews, while quantitative research tests hypotheses using numerical data and statistical analysis.

What are the four levels of measurement in statistics?

Nominal, Ordinal, Interval, and Ratio.

Describe a nominal level of measurement.

Categorical data without any intrinsic order or numerical significance.

How is an ordinal level of measurement characterized?

Categorical data with a meaningful order but with unequal or undefined intervals between categories.

What distinguishes an interval level of measurement?

Ordered data with equal intervals between values, but without a true zero point, meaning ratios are not meaningful.

What is a ratio level of measurement?

Ordered data with equal intervals and a true absolute zero point, allowing for meaningful ratios.

What does the Central Limit Theorem state?

For a sufficiently large sample size, the sampling distribution of the sample mean will be approximately normally distributed, regardless of the population's distribution, and its mean will be the population mean.

What is a null hypothesis ($H\_0$)?

A statistical hypothesis that states there is no significant difference, relationship, or effect between specified populations or observed phenomena, serving as a baseline for testing.

What is an alternative hypothesis ($H\_1$)?

A statistical hypothesis that contradicts the null hypothesis, stating that there is a significant difference, relationship, or effect.

Define a Type I error in hypothesis testing.

The error of rejecting a true null hypothesis ($H\_0$), often referred to as a false positive.

Define a Type II error in hypothesis testing.

The error of failing to reject a false null hypothesis ($H\_0$), often referred to as a false negative.

What is an effect size?

A quantitative measure of the magnitude of a phenomenon, such as the strength of a relationship between two variables or the difference between two groups.

What is internal validity in research?

The extent to which a study accurately establishes a cause-and-effect relationship, ensuring that observed changes in the dependent variable are due to the independent variable and not other factors.

What is external validity in research?

The extent to which the findings of a study can be generalized to other populations, settings, and situations.

What is the primary difference between descriptive and inferential statistics?

Descriptive statistics summarize and describe the characteristics of a dataset, while inferential statistics use sample data to make predictions or draw conclusions about a larger population.

What are the three common measures of central tendency?

The Mean, Median, and Mode.

How is the mean calculated?

By summing all values in a dataset and dividing by the total number of values.

What is the median of a dataset?

The middle value in a dataset when it is ordered from least to greatest; if there's an even number of values, it's the average of the two middle values.

What is the mode of a dataset?

The value that appears most frequently in a dataset.

Why is distinguishing between correlation and causation critical in research?

Correlation only indicates that two variables move together, not that one variable causes a change in the other. Causation implies a direct cause-and-effect relationship, which requires more rigorous evidence, often from experimental designs.

What is standard deviation?

A measure of the dispersion or spread of a set of data values around the mean; a low standard deviation indicates values are close to the mean, while a high standard deviation indicates values are spread out.