Stats for Beginners

Enter and organize a small dataset in Excel using labels, values, cell references, and basic formulas.

Create a frequency table and histogram from raw data in Excel.

Calculate and interpret the mean, median, and mode of a dataset.

Calculate and interpret the range, variance, and standard deviation of a dataset.

Use Excel functions to calculate measures of center and variation.

Calculate a z-score and use it to compare relative positions in different datasets.

Determine quartiles, the interquartile range, and potential outliers, then display them in a boxplot.

Choose appropriate numerical and graphical summaries based on a distribution's shape and outliers.

Represent the possible outcomes of a chance process with a sample space and events.

Calculate the probability of an event's complement.

Apply the general addition rule to calculate the probability of either of two events.

Calculate conditional probabilities from counts or a two-way table.

Apply the multiplication rule to calculate the probability of a sequence of events.

Determine whether two events are independent.

Organize multistage probabilities with a tree diagram or table.

Choose and apply the fundamental counting rule, permutations, or combinations in a counting problem.

Verify that a table defines a valid discrete probability distribution.

Calculate the mean, variance, and standard deviation of a discrete random variable.

Determine whether a scenario satisfies the requirements of a binomial experiment.

Calculate an exact binomial probability using the binomial formula and a basic calculator.

Calculate exact and cumulative binomial probabilities with Excel and the complement rule.

Use a binomial distribution's mean and standard deviation to identify unusual results.

Determine whether a count scenario can be modeled with a Poisson distribution and identify its rate parameter.

Calculate and interpret a Poisson probability using a basic calculator or Excel.

Identify the center, spread, and symmetry of a normal distribution from its parameters and graph.

Standardize a normal measurement by calculating its z-score.

Use a standard normal table to find an area or probability from a z-score.

Find a z-score corresponding to a given cumulative area or percentile.

Calculate probabilities for a nonstandard normal variable.

Find a cutoff value or percentile in a nonstandard normal distribution.

Apply a continuity correction when using a normal model to approximate a binomial probability.

Assess approximate normality using a histogram and a normal quantile plot.

Distinguish a population distribution, a sample distribution, and a sampling distribution.

Describe the sampling distribution of the sample mean.

Calculate the mean and standard error of a sample-mean distribution.

Use the Central Limit Theorem to determine when a sample-mean distribution is approximately normal.

Calculate a probability involving a sample mean.

Calculate the mean and standard error of a sample-proportion distribution.

Calculate a probability involving a sample proportion.

Predict how increasing sample size changes sampling variability.

Interpret a confidence level and confidence interval in the context of repeated sampling.

Calculate a critical value and margin of error for a confidence interval.

Check the conditions required for a one-sample confidence interval for a population mean.

Construct a one-sample confidence interval for a population mean using the t distribution.

Check the conditions required for a one-sample confidence interval for a population proportion.

Construct a one-sample confidence interval for a population proportion.

Determine a sample size needed to estimate a mean or proportion with a specified margin of error.

Use Excel confidence-interval output to report an estimate in context.

Translate a verbal claim into null and alternative hypotheses and identify the test direction.

Distinguish Type I and Type II errors in the context of a decision.

Calculate and interpret a test statistic and p-value.

Make a significance decision and state the conclusion in the language of the original claim.

Conduct a one-sample t test for a population mean using a basic calculator.

Conduct a one-sample z test for a population proportion using a basic calculator.

Use Excel output to conduct and document a one-sample hypothesis test.

Distinguish statistical significance from practical significance.

Distinguish independent samples from paired data in a study description.

Construct a confidence interval for the difference between two independent population means.

Conduct a hypothesis test comparing two independent population means.

Convert paired observations into a single sample of differences and check its conditions.

Conduct a paired t procedure and interpret the result in context.

Construct a confidence interval for the difference between two population proportions.

Conduct a hypothesis test comparing two population proportions.

Select the appropriate two-sample procedure for a given study design and variable type.

State the hypotheses of a one-way analysis of variance in context.

Check the independence, normality, and equal-variation conditions for one-way ANOVA.

Conduct a one-way ANOVA in Excel and interpret its F statistic and p-value.

Distinguish a chi-square goodness-of-fit question from a chi-square test-of-independence question.

Calculate expected counts for a chi-square goodness-of-fit test.

Conduct and interpret a chi-square goodness-of-fit test.

Calculate expected counts in a contingency table.

Conduct and interpret a chi-square test of independence.

Create and interpret a scatterplot for two quantitative variables.

Calculate and interpret the direction and strength of a linear correlation coefficient.

Explain why correlation does not by itself establish causation.

Conduct a hypothesis test for linear correlation.

Fit a least-squares regression line using Excel.

Interpret the slope and intercept of a regression line in context.

Use a regression equation for prediction while recognizing extrapolation.

Assess a regression model using residuals, outliers, and the coefficient of determination.

Translate a statistical word problem into known quantities, an unknown target, and relevant variables.

Select an appropriate descriptive or inferential method from the full STAT 1P98 toolkit.

Verify the assumptions and conditions for a selected statistical procedure using a checklist.

Carry out a probability or inference calculation with a permitted basic calculator while showing all required steps.

Check whether a statistical calculation is plausible using estimation, units, and probability bounds.

Perform a complete Excel analysis on an ungraded real-world dataset.

Write a concise, plain-language interpretation of statistical output without overstating the evidence.

Diagnose and correct conceptual or computational errors in a completed mixed-topic solution.