We are allowed to do 2 practice exams before the actual exam. the actual exam is tomorrow starting 8 am - 11:00 am were going to have 3 hours to finished it its going to be 31 questions exam. the practice test is the same questions but with different numbers we can practice the questions so were ready for tomorrow I will send you the teachers way how to solve them we have to do exactly the way she did if we don't do like she did she won't give me full points on the exam.
The exam covers these topics:
Canvas Module: Introduction to Statistics (Section 01)
- Definitions: population, parameter, sample, statistic, census
- Data Types: Categorical/Quantitative, Discrete/Continuous
- Levels of Measurement: Nominal/Ordinal/Interval/Ratio
- Study Types: Observational/Experimental
- Sampling Techniques: Random/Simple Random/Stratified/Systematic/Cluster/Convenience/Multistage
Canvas Module: Exploring Data with Tables and Graphs (Section 02)
- Definition: Distribution
- Frequency Distribution Elements: Lower Class Limit/Upper Class Limit/Class Boundaries/Class Midpoints/Class Width/Relative Frequency
- Creating a Frequency Distribution from Data: with a class start and a class width/with a given number of classes
- Graphing: Frequency Histograms/Relative Frequency Histograms/Frequency Polygons/Relative Frequency Polygons
Canvas Module: Describing, Exploring, and Comparing Data (Sections 03 and 04)
- Understanding and Calculating Measures of Center: Arithmetic Mean/Median/Mode/Frequency Distribution Mean
- Understanding and Calculating Measures of Variation: Standard Deviation/Variance/Range/Frequency Distribution Standard Deviation
- Empirical Rule/Chebyshev’s Theorem
- Calculation and Interpretation of Z-score from data value
- Calculation and Interpretation of data value from Z-score
- Unusual/Not unusual
- Calculation and Interpretation of percentile from data value
- Calculation and Interpretation of data value from percentile
- Five Number Summary/Constructing Boxplots
Canvas Module: Probability (Sections 05, 06, and 07)
- Definitions: Probability/Event/Simple Event/Sample Space/Sample Size
- Classical Probability/Relative Frequency Probability
- Law of Large Numbers
- Certain/Likely/50-50/Unlikely/Impossible
- Compound/Disjoint/Mutually Exclusive/Independent/Dependent
- Complement/At Least/At Most/More Than/Fewer Than
- Addition Rule
- Multiplication Rule
- Conditional Probability
- Bayes’ Theorem
- Counting: Multiplication Rule/Factorial Rule/Permutation Rule/Identical Item Rule/Combination Rule
Canvas Module: Discrete Probability Distributions (Sections 08 and 09)
- Definitions: Discrete Random Variable/Discrete Probability Distribution
- Determine if a distribution is a probability distribution or how to make a distribution into a probability distribution
- Construct a probability histogram
- Probability Distribution: Construct a probability histogram/Find Mean/Find Standard Deviation
- Calculate/Interpret/Explain Expectation
- Binomial Distribution/Calculation/Mean/Standard Deviation
- Poisson Distribution/Calculation/Mean/Standard Deviation
- Binomial Approximation with the Poisson Distribution Justification/Calculation
- Significantly High/Significantly Low
- Apply Complement/At Least/At Most/More Than/Fewer Than to Section 08 and 09 concepts
- Apply z-score/unusual/not unusual to Section 08 and 09 concepts
Canvas Module: Normal Probability Distributions (Sections 10, 11, and 12)
- Definitions: Continuous Random Variable/Continuous Probability Distribution/Density Curve
- Standard Normal Distribution/Normal Distribution
- Find a probability/area from a z-score/data value using tables or technology
- Find a z-score/data value from a probability/area using tables or technology
- Definition: Proportion
- Understand Sampling Distributions and Techniques
- Understand which statistics target which parameters and why
- Central Limit Theorem
- Apply Central Limit Theorem to probability calculations associated with the mean of a group of data points.
- Apply percentiles to Section 10, 11, and 12 concepts
- Apply Complement/At Least/At Most/More Than/Fewer Than to Section 10, 11, and 12 concepts
- Understand and Interpret Normal Quartile Plots
- Binomial Approximation with the Normal Distribution Justification/Calculation
- Apply z-score/unusual/not unusual to Section 10, 11, and 12 concepts
- Apply significantly low/significantly high to Section 10, 11, and 12 concepts
- Determine how to solve a problem and justify the choice: Binomial Distribution/Binomial Approximation with the Poisson Distribution/Binomial Approximation with the Poisson Distribution
Canvas Module: Estimating Parameters and Determining Sample Sizes (Sections 13 and 14)
- Definitions: Point Estimate/Confidence Level/Confidence Interval/Critical Value/Margin of Error
- Understand and Interpret Confidence Intervals
- Find Confidence Intervals for Proportion
- Find Sample Sizes required to estimate Population Proportion with/without a point estimate for Population Proportion
- Definition: Degrees of Freedom
- Find a probability/area or range from a t-score/data value using tables or technology
- Find a t-score/data value or range from a probability/area using tables or technology
- Find Confidence Intervals for Mean with/without the Population Standard Deviation
- Find Sample Sizes required to estimate Population Mean
- Find a probability/area or range from a x2-score/data value using tables or technology
- Find a x2-score/data value or range from a probability/area using tables or technology
- Find Confidence Intervals for Standard Deviation
- Find Sample Sizes required to estimate Population Standard Deviation
- Apply Calculation Techniques from Section 03 to find Mean/Standard Deviation of data
Canvas Module: Hypothesis Testing (Sections 15 and 16)
- Definitions: Hypothesis/Hypothesis Test/Null Hypothesis/Alternative Hypothesis/Significance Level/Critical Region/Critical Value/Test Statistic/p-Value
- Understanding and Application of Critical Value Method of Hypothesis Testing using tables or technology
- Understanding and Application of p-Value Method of Hypothesis Testing using tables or technology
- One-Population Proportion Hypothesis Testing
- One-Population Mean Hypothesis Testing with/without the Population Standard Deviation
- One-Population Standard Deviation/Variance Hypothesis Testing
- Apply Calculation Techniques from Section 03 to find Mean/Standard Deviation of data
Canvas Module: Inferences from Two Samples (Sections 17 and 18)
- Two-Population Proportion Hypothesis Testing
- Determine whether two-population data is independent or matched pairs
- Two-Population Mean Hypothesis Testing with/without the Population Standard Deviations
- Find a probability/area or range from a F-score/data value using tables or technology
- Find a F-score/data value or range from a probability/area using tables or technology
- Two-Population Standard Deviation/Variance Hypothesis Testing
- Apply Calculation Techniques from Section 03 to find Mean/Standard Deviation of data
Canvas Module: Correlation and Regression (Sections 19 and 20)
- Definitions: Correlation/Linear Correlation/Scatterplot
- Calculate and Interpret the Pearson Product Moment/Linear Correlation Coefficient/Coefficient of Determination
- Linear Correlation Hypothesis Testing using the critical value table
- Find the Linear Regression Line
- Predict the value of the response/dependent variable using either the linear regression line or the sample mean of the dependent variable data justifying the method of choice
Canvas Module: Goodness-of-Fit and Contingency Tables (Section 21)
- Goodness-Of-Fit Hypothesis Testing
- Independence Hypothesis Testing
- Homogeneity Hypothesis Testing
Canvas Module: Analysis of Variance (Section 22)
- One-Way ANOVA Hypothesis Testing where all samples have the same sample size