Statistics Chapter 5 Quiz

<p>It provides a range of values based on a sample statistic. (D)</p> Signup and view all the answers

<p>To compute point estimates and confidence intervals for sample statistics. (C)</p> Signup and view all the answers

<p>They provide a summary of the data using measures such as proportions and percentages. (D)</p> Signup and view all the answers

<p>To identify the most frequently occurring value in nominal data. (D)</p> Signup and view all the answers

<p>Median (C)</p> Signup and view all the answers

<p>Descriptive statistics using ratios. (D)</p> Signup and view all the answers

<p>The value that separates the highest half from the lowest half. (C)</p> Signup and view all the answers

<p>Proportions represent a part of a whole, whereas ratios reflect relative size comparisons. (B)</p> Signup and view all the answers

<p>Measure of central tendency (B)</p> Signup and view all the answers

<p>Nominal data only (C)</p> Signup and view all the answers

<p>To summarize and describe the distribution of single or multiple variables (A)</p> Signup and view all the answers

<p>Generalize findings from a sample to a larger population (B)</p> Signup and view all the answers

<p>Summarizes data from only one variable (C)</p> Signup and view all the answers

<p>Establishing clear conceptual definitions (A)</p> Signup and view all the answers

<p>Any characteristic or attribute that can vary among subjects (A)</p> Signup and view all the answers

<p>Random sampling (C)</p> Signup and view all the answers

<p>To determine the validity of a statistical hypothesis (C)</p> Signup and view all the answers

<p>Standard deviation (D)</p> Signup and view all the answers

<p>Exhaustiveness (C)</p> Signup and view all the answers

<p>Discrete variables have distinct and separate values. (D)</p> Signup and view all the answers

<p>Hypothesis Development (D)</p> Signup and view all the answers

<p>Categories must overlap. (B)</p> Signup and view all the answers

<p>Categories must be consistent in measuring the same attribute. (B)</p> Signup and view all the answers

<p>The score that occurs most frequently (C)</p> Signup and view all the answers

<p>When data includes extreme outliers (A)</p> Signup and view all the answers

<p>Comparison of categories in terms of relative frequency (B)</p> Signup and view all the answers

<p>Nominal level data (C)</p> Signup and view all the answers

<p>To summarize large sets of data into simpler forms (C)</p> Signup and view all the answers

<p>They allow for comparison of parts of a whole (D)</p> Signup and view all the answers

<p>Median (B)</p> Signup and view all the answers

<p>Descriptive statistics (C)</p> Signup and view all the answers

<p>They allow for the generalization from a sample to a population (B)</p> Signup and view all the answers

<p>Any characteristic that can take different values (B)</p> Signup and view all the answers

<p>Developing accurate measurement tools for concepts (B)</p> Signup and view all the answers

<p>They summarize distribution of a single variable (D)</p> Signup and view all the answers

<p>They indicate the strength of a relationship between two variables (A)</p> Signup and view all the answers

<p>Examining relationships between two variables (A)</p> Signup and view all the answers

<p>Choosing the most appropriate variables for the research objective (C)</p> Signup and view all the answers

<p>It guarantees a representative sample of the population (B)</p> Signup and view all the answers

<p>It requires the formulation of two opposing hypotheses (D)</p> Signup and view all the answers

<p>Construct a normal curve by increasing sample size. (D)</p> Signup and view all the answers

<p>To summarize data with a single statistic. (B)</p> Signup and view all the answers

<p>A statistic that provides information about a sample. (D)</p> Signup and view all the answers

<p>A range of values indicating potential population estimates. (C)</p> Signup and view all the answers

<p>100 (C)</p> Signup and view all the answers

<p>To produce reliable estimates of population parameters. (D)</p> Signup and view all the answers

<p>To facilitate the application of inferential statistics. (D)</p> Signup and view all the answers

<p>They show how sample means vary from the population mean. (D)</p> Signup and view all the answers

<p>The hypothesis must be falsifiable and testable. (D)</p> Signup and view all the answers

<p>Median (D)</p> Signup and view all the answers

<p>95% (B)</p> Signup and view all the answers

<p>It shows that 47.72% of the area is between it and the mean. (D)</p> Signup and view all the answers

<p>To generalize sample statistics to the population. (C)</p> Signup and view all the answers

<p>EPSEM (Equal Probability of Selection Method) (B)</p> Signup and view all the answers

<p>Populations are too large to measure directly. (B)</p> Signup and view all the answers

<p>0.05 (B)</p> Signup and view all the answers

<p>The difference between the population mean and the sample mean. (A)</p> Signup and view all the answers

<p>The score is below the mean. (D)</p> Signup and view all the answers

<p>It is always symmetrical around the mean. (C)</p> Signup and view all the answers

<p>The score is equal to the mean. (D)</p> Signup and view all the answers

If a population isn't normally distributed, a normal curve can still be used for large samples.

Generally, a sample size of at least 100 is needed for the Central Limit Theorem to apply.

The distribution of sample statistics from a population for many samples.

A sample statistic used to estimate a population value.

A range of values (an interval) used to estimate a population value.

A starting point for statistical analysis used to summarize a single variable with many observations.

Statistics that summarize a dataset. Examples include proportions, percentages, rates, and ratios.

Used to standardize raw data and compare parts of a whole, or compare groups of different sizes.

Used to compare categories of a variable in terms of relative frequency or to summarize a single-variable distribution.

Statistics that describe the typical or average case in a data distribution.

The most frequent score in a data distribution. Used primarily with nominal data.

The exact middle score in a data distribution, with half of the values above and half below.

Categorical data without any inherent order or ranking.

Clearly defining a concept for research purposes by specifying its characteristics and boundaries.

Defining a concept in a way that can be measured or observed in a study.

Methods allowing researchers to generalize findings from a sample to a larger population.

Describing the relationships between two or more variables.

Gathering information to measure the concept being studied or using existing data.

Collecting data through surveys or compiling data from existing sources or datasets.

The most frequently occurring score in a dataset. It's particularly useful for nominal data, where order doesn't matter.

The middle score in a dataset when it's ordered from least to greatest. It's most useful for ordinal data, where scores have a natural order.

Statistics that help describe the 'typical' or 'average' case in a dataset. They summarize the center or most representative value of a distribution.

Categorical data with no inherent order or ranking. Think of categories that are simply different, not better or worse.

Statistics that summarize a dataset. They provide an overview of the data, but don't draw conclusions about a larger population.

To standardize raw data. They compare parts of a whole, or groups of different sizes.

To compare categories of a variable in terms of relative frequency, or to summarize the distribution of a single variable.

Statistics that summarize a single variable with many observations. They are a starting point for further statistical analysis.

A statistic calculated from a sample that is used to estimate a population parameter.

An estimator that, on average, provides a value that is equal to the true population parameter.

An estimator that has the smallest possible variance among all unbiased estimators.

A bell-shaped distribution that describes the probability of a random variable taking on different values.

A characteristic of the entire population that we want to estimate.

The scientific method, used to study the natural world, is also applied to social science research. However, the social world has more "noise", meaning more factors influence results, making it less controllable.

Variables are characteristics that change in value across individuals or cases in a study. They are essential for understanding relationships and patterns in social phenomena.

Response categories for a variable should be mutually exclusive. This means each category is distinct and doesn't overlap with others.

Response categories for a variable must cover all possible values or outcomes. No potential answer should be left out.

Response categories within a variable should be consistent in nature. They should all measure the same thing to avoid confusing the results.

A standardized score that represents the distance of a data point from the mean, measured in standard deviations.

The average distance of data points from the mean.

The process of selecting a subset (a sample) from a larger population to study and draw conclusions about.

A sample selected using a random method, ensuring each member of the population has a known chance of being chosen.

A clear, measurable definition of a concept used in research. It specifies how the concept will be observed and measured in a study.

The difference between the characteristics of a sample and the characteristics of the population from which it was drawn.

Methods used to gather information for a study, such as surveys, interviews, or collecting existing data.

Equal Probability of Selection Method

A Z score of +2 indicates a data point that is two standard deviations above the mean.

Samples are used because it is often impractical or impossible to study the entire population.

A sampling distribution allows researchers to generalize findings from a sample to the population.

Descriptive statistics summarize data, while inferential statistics use data to make inferences about a population.

It indicates the most common value in a distribution, representing the peak of a frequency distribution.

It represents the center point of a distribution, dividing the data into two halves with equal numbers of values above and below.