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😼AP Statistics Unit 7 Vocabulary

139 essential vocabulary terms and definitions for Unit 7 – Means

Study Unit 7
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😼Unit 7 – Means
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😼Unit 7 – Means

7.1 Introducing Statistics

TermDefinition
probabilities of errorsThe likelihood or chance that errors will occur in statistical inference.
statistical inferenceThe process of drawing conclusions about a population based on data collected from a sample.
variationDifferences in data that occur by chance due to the random nature of sampling, rather than from systematic causes.

7.2 Constructing a Confidence Interval for a Population Mean

TermDefinition
confidence intervalA range of values, calculated from sample data, that is likely to contain the true population parameter with a specified level of confidence.
confidence interval procedureA statistical method used to construct an interval estimate for a population parameter based on sample data.
critical valueA value from the standard normal distribution used to determine the margin of error for a given confidence level.
degrees of freedomA parameter of the t-distribution that affects its shape; as degrees of freedom increase, the t-distribution approaches the normal distribution.
density curveA graphical representation of a probability distribution showing the relative likelihood of different values.
independenceThe condition that observations in a sample are not influenced by each other, typically ensured through random sampling or randomized experiments.
margin of errorThe amount by which a sample statistic is likely to vary from the corresponding population parameter, calculated as the critical value times the standard error.
matched pairsPaired observations where two measurements are taken on the same subject or on subjects that are matched according to specific criteria, used to analyze the mean difference between the paired values.
mean differenceThe average of the differences between paired observations, denoted by μd, where the order of subtraction must be clearly defined.
normal distributionA probability distribution that is mound-shaped and symmetric, characterized by a population mean (μ) and population standard deviation (σ).
one-sample t-intervalA confidence interval for a population mean constructed using the t-distribution when the population standard deviation is unknown.
outlierData points that are unusually small or large relative to the rest of the data.
population meanThe average of all values in an entire population, denoted as μ.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
population standard deviationA measure of the spread or dispersion of all values in a population, denoted by σ, which is a parameter of the normal distribution.
random sampleA sample selected from a population in such a way that every member has an equal chance of being chosen, reducing bias and allowing for valid statistical inference.
randomized experimentA study design where subjects are randomly assigned to treatment groups to establish cause-and-effect relationships.
sample meanThe average of all values in a sample, denoted as x̄, used as an estimate of the population mean.
sample sizeThe number of observations or data points collected in a sample, denoted as n.
sample standard deviationThe standard deviation calculated for a sample, denoted by s, using the formula s = √(1/(n-1) ∑(xᵢ-x̄)²).
sample statisticA numerical value calculated from sample data that is used to estimate the corresponding population parameter.
sampling distributionThe probability distribution of a sample statistic (such as a sample proportion) obtained from repeated sampling of a population.
sampling without replacementA sampling method in which an item selected from a population cannot be selected again in subsequent draws.
skewnessA measure of the asymmetry of a distribution, indicating whether data is concentrated more on one side of the center.
standard errorThe standard deviation of a sampling distribution, which measures the variability of a sample statistic across repeated samples.
t-distributionA probability distribution used when the population standard deviation is unknown and the sample standard deviation is used instead, characterized by heavier tails than the normal distribution.
tailsThe extreme regions at both ends of a probability distribution's density curve where the t-distribution allocates more area than the normal distribution.

7.3 Justifying a Claim About a Population Mean Based on a Confidence Interval

TermDefinition
confidence intervalA range of values, calculated from sample data, that is likely to contain the true population parameter with a specified level of confidence.
confidence levelThe probability that a confidence interval will contain the true population parameter, typically expressed as a percentage such as 90%, 95%, or 99%.
margin of errorThe amount by which a sample statistic is likely to vary from the corresponding population parameter, calculated as the critical value times the standard error.
matched pairsPaired observations where two measurements are taken on the same subject or on subjects that are matched according to specific criteria, used to analyze the mean difference between the paired values.
populationThe entire group of individuals or items from which a sample is drawn and about which conclusions are to be made.
population meanThe average of all values in an entire population, denoted as μ.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
random sampleA sample selected from a population in such a way that every member has an equal chance of being chosen, reducing bias and allowing for valid statistical inference.
sampleA subset of individuals or items selected from a population for the purpose of data collection and analysis.
sample sizeThe number of observations or data points collected in a sample, denoted as n.
width of a confidence intervalThe range or span of a confidence interval, calculated as the difference between the upper and lower bounds of the interval.

7.4 Setting Up a Test for a Population Mean

TermDefinition
10% conditionThe requirement that sample size n is at most 10% of the population size N to ensure independence when sampling without replacement.
alternative hypothesisThe claim that contradicts the null hypothesis, representing what the researcher is trying to find evidence for.
approximately normalA distribution that closely follows the shape of a normal distribution, allowing for the use of normal probability methods.
conditions for the testThe requirements that must be satisfied before conducting a hypothesis test for a population mean, including independence and normality of the sampling distribution.
independenceThe condition that observations in a sample are not influenced by each other, typically ensured through random sampling or randomized experiments.
matched pairsPaired observations where two measurements are taken on the same subject or on subjects that are matched according to specific criteria, used to analyze the mean difference between the paired values.
mean differenceThe average of the differences between paired observations, denoted by μd, where the order of subtraction must be clearly defined.
null hypothesisThe initial claim or assumption being tested in a hypothesis test, typically stating that there is no effect or no difference.
one-sample t-testA hypothesis test used to determine whether a population mean differs from a hypothesized value when the population standard deviation is unknown.
outlierData points that are unusually small or large relative to the rest of the data.
population meanThe average of all values in an entire population, denoted as μ.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
random sampleA sample selected from a population in such a way that every member has an equal chance of being chosen, reducing bias and allowing for valid statistical inference.
randomized experimentA study design where subjects are randomly assigned to treatment groups to establish cause-and-effect relationships.
sample sizeThe number of observations or data points collected in a sample, denoted as n.
sampling distributionThe probability distribution of a sample statistic (such as a sample proportion) obtained from repeated sampling of a population.
sampling without replacementA sampling method in which an item selected from a population cannot be selected again in subsequent draws.
significance testA statistical procedure used to determine whether there is sufficient evidence to reject the null hypothesis based on sample data.
skewnessA measure of the asymmetry of a distribution, indicating whether data is concentrated more on one side of the center.

7.5 Carrying Out a Test for a Population Mean

TermDefinition
degrees of freedomA parameter of the t-distribution that affects its shape; as degrees of freedom increase, the t-distribution approaches the normal distribution.
matched pairsPaired observations where two measurements are taken on the same subject or on subjects that are matched according to specific criteria, used to analyze the mean difference between the paired values.
null hypothesisThe initial claim or assumption being tested in a hypothesis test, typically stating that there is no effect or no difference.
p-valueThe probability of observing a test statistic as extreme as or more extreme than the one calculated from the sample data, assuming the null hypothesis is true.
population meanThe average of all values in an entire population, denoted as μ.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
reject the null hypothesisThe decision made when the p-value is less than or equal to the significance level, indicating sufficient evidence against the null hypothesis.
sample meanThe average of all values in a sample, denoted as x̄, used as an estimate of the population mean.
sampling distributionThe probability distribution of a sample statistic (such as a sample proportion) obtained from repeated sampling of a population.
significance levelThe threshold probability (α) used to determine whether to reject the null hypothesis in a significance test.
significance testA statistical procedure used to determine whether there is sufficient evidence to reject the null hypothesis based on sample data.
standard errorThe standard deviation of a sampling distribution, which measures the variability of a sample statistic across repeated samples.
t-distributionA probability distribution used when the population standard deviation is unknown and the sample standard deviation is used instead, characterized by heavier tails than the normal distribution.
test statisticA calculated value used to determine whether to reject the null hypothesis in a hypothesis test, computed from sample data.

7.6 Confidence Intervals for the Difference of Two Means

TermDefinition
approximately normalA distribution that closely follows the shape of a normal distribution, allowing for the use of normal probability methods.
confidence intervalA range of values, calculated from sample data, that is likely to contain the true population parameter with a specified level of confidence.
confidence interval procedureA statistical method used to construct an interval estimate for a population parameter based on sample data.
critical valueA value from the standard normal distribution used to determine the margin of error for a given confidence level.
degrees of freedomA parameter of the t-distribution that affects its shape; as degrees of freedom increase, the t-distribution approaches the normal distribution.
difference of population meansThe difference between the mean values of two distinct populations, calculated as μ₁ - μ₂.
independenceThe condition that observations in a sample are not influenced by each other, typically ensured through random sampling or randomized experiments.
independent samplesTwo or more separate groups of data where the values in one group do not influence or depend on the values in another group.
margin of errorThe amount by which a sample statistic is likely to vary from the corresponding population parameter, calculated as the critical value times the standard error.
normal distributionA probability distribution that is mound-shaped and symmetric, characterized by a population mean (μ) and population standard deviation (σ).
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
population standard deviationsThe measure of spread in each of two populations; when unknown, sample standard deviations are used as estimates.
quantitative variableA variable that is measured numerically and can take on a range of values, allowing for mathematical operations and statistical analysis.
randomized experimentA study design where subjects are randomly assigned to treatment groups to establish cause-and-effect relationships.
sample meanThe average of all values in a sample, denoted as x̄, used as an estimate of the population mean.
sample standard deviationsThe measures of variability within each of the two samples, denoted as s₁ and s₂.
sample statisticA numerical value calculated from sample data that is used to estimate the corresponding population parameter.
sampling distributionThe probability distribution of a sample statistic (such as a sample proportion) obtained from repeated sampling of a population.
sampling without replacementA sampling method in which an item selected from a population cannot be selected again in subsequent draws.
simple random sampleA sample selected from a population such that every possible sample of the same size has an equal chance of being chosen.
skewed distributionsDistributions that are not symmetric, with data concentrated on one side and a tail extending to the other side.
standard errorThe standard deviation of a sampling distribution, which measures the variability of a sample statistic across repeated samples.
t-distributionA probability distribution used when the population standard deviation is unknown and the sample standard deviation is used instead, characterized by heavier tails than the normal distribution.
two-sample t-intervalA confidence interval procedure used to estimate the difference between two population means using sample data from two independent samples.

7.7 Justifying a Claim About the Difference of Two Means Based on a Confidence Interval

TermDefinition
confidence intervalA range of values, calculated from sample data, that is likely to contain the true population parameter with a specified level of confidence.
difference in sample meansThe result of subtracting one sample mean from another sample mean, calculated as x̄₁ - x̄₂.
difference of population meansThe difference between the mean values of two distinct populations, calculated as μ₁ - μ₂.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
random samplingA method of selecting samples from a population where each member has an equal chance of being chosen, ensuring the sample is representative of the population.
sample sizeThe number of observations or data points collected in a sample, denoted as n.
width of a confidence intervalThe range or span of a confidence interval, calculated as the difference between the upper and lower bounds of the interval.

7.8 Setting Up a Test for the Difference of Two Population Means

TermDefinition
alternative hypothesisThe claim that contradicts the null hypothesis, representing what the researcher is trying to find evidence for.
approximately normalA distribution that closely follows the shape of a normal distribution, allowing for the use of normal probability methods.
difference of population meansThe difference between the mean values of two distinct populations, calculated as μ₁ - μ₂.
independenceThe condition that observations in a sample are not influenced by each other, typically ensured through random sampling or randomized experiments.
null hypothesisThe initial claim or assumption being tested in a hypothesis test, typically stating that there is no effect or no difference.
outlierData points that are unusually small or large relative to the rest of the data.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
quantitative variableA variable that is measured numerically and can take on a range of values, allowing for mathematical operations and statistical analysis.
randomized experimentA study design where subjects are randomly assigned to treatment groups to establish cause-and-effect relationships.
sampling distributionThe probability distribution of a sample statistic (such as a sample proportion) obtained from repeated sampling of a population.
sampling without replacementA sampling method in which an item selected from a population cannot be selected again in subsequent draws.
significance testA statistical procedure used to determine whether there is sufficient evidence to reject the null hypothesis based on sample data.
simple random sampleA sample selected from a population such that every possible sample of the same size has an equal chance of being chosen.
skewnessA measure of the asymmetry of a distribution, indicating whether data is concentrated more on one side of the center.
two-sample t-testA statistical test used to determine whether there is a significant difference between the means of two independent population samples.

7.9 Carrying Out a Test for the Difference of Two Population Means

TermDefinition
degrees of freedomA parameter of the t-distribution that affects its shape; as degrees of freedom increase, the t-distribution approaches the normal distribution.
difference in sample meansThe result of subtracting one sample mean from another sample mean, calculated as x̄₁ - x̄₂.
difference of population meansThe difference between the mean values of two distinct populations, calculated as μ₁ - μ₂.
normal distributionA probability distribution that is mound-shaped and symmetric, characterized by a population mean (μ) and population standard deviation (σ).
null hypothesisThe initial claim or assumption being tested in a hypothesis test, typically stating that there is no effect or no difference.
p-valueThe probability of observing a test statistic as extreme as or more extreme than the one calculated from the sample data, assuming the null hypothesis is true.
population meansThe average values of two distinct populations being compared, denoted as μ₁ and μ₂.
quantitative variableA variable that is measured numerically and can take on a range of values, allowing for mathematical operations and statistical analysis.
randomized experimentA study design where subjects are randomly assigned to treatment groups to establish cause-and-effect relationships.
reject the null hypothesisThe decision made when the p-value is less than or equal to the significance level, indicating sufficient evidence against the null hypothesis.
sampling distributionThe probability distribution of a sample statistic (such as a sample proportion) obtained from repeated sampling of a population.
significance levelThe threshold probability (α) used to determine whether to reject the null hypothesis in a significance test.
significance testA statistical procedure used to determine whether there is sufficient evidence to reject the null hypothesis based on sample data.
simple random sampleA sample selected from a population such that every possible sample of the same size has an equal chance of being chosen.
standard errorThe standard deviation of a sampling distribution, which measures the variability of a sample statistic across repeated samples.
statistical reasoningThe logical process of using sample data and significance test results to draw conclusions about populations and answer research questions.
t-distributionA probability distribution used when the population standard deviation is unknown and the sample standard deviation is used instead, characterized by heavier tails than the normal distribution.
test statisticA calculated value used to determine whether to reject the null hypothesis in a hypothesis test, computed from sample data.
two-sample testA significance test used to compare the means of two different populations based on sample data from each population.