Learning AP Statistics with TI-Nspire (***)

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UNIT 1: Exploring One-Variable Data

UNIT 2: Exploring Two-Variable Data

UNIT 3: Collecting Data

UNIT 4: Probability, Random Variables, and Probability Distributions

UNIT 5: Sampling Distributions

UNIT 6: Inference for Categorical Data: Proportions

UNIT 7: Inference for Quantitative Data: Means

UNIT 8: Inference for Categorical Data: Chi-Square

UNIT 9: Inference for Quantitative Data: Slopes

UNIT 1: Exploring One-Variable Data

1.1 Introducing Statistics: What Can We Learn from Data?

1.2 The Language of Variation: Variables

1.3 Representing a Categorical Variable with Tables

1.4 Representing a Categorical Variable with Graphs

1.5 Representing a Quantitative Variable with Graphs

1.6 Describing the Distribution of a Quantitative Variable

1.7 Summary Statistics for a Quantitative Variable

1.8 Graphical Representations of Summary Statistics

1.9 Comparing Distributions of a Quantitative Variable

1.10 The Normal Distribution

UNIT 2: Exploring Two-Variable Data

2.1 Introducing Statistics: Are Variables Related?

2.2 Representing Two Categorical Variables

2.3 Statistics for Two Categorical Variables

2.4 Representing the Relationship Between Two Quantitative Variables

2.5 Correlation

# Scatter Plot, Linear Reg, Correlation & Residuals with TI-NSPIRE

2.6 Linear Regression Models

#Least Squares Regression Line (LSRL) - AP Statistics - Avon High School

2.7 Residuals

2.8 Least Squares Regression

2.9 Analyzing Departures from Linearity

UNIT 3: Collecting Data

3.1 Introducing Statistics: Do the Data We Collected Tell the Truth?

3.2 Introduction to Planning a Study

3.3 Random Sampling and Data Collection

3.4 Potential Problems with Sampling

3.5 Introduction to Experimental Design

3.6 Selecting an Experimental Design

3.7 Inference and Experiments

UNIT 4: Probability, Random Variables, and Probability Distributions

4.1 Introducing Statistics: Random and Non-Random Patterns?

4.2 Estimating Probabilities Using Simulation

4.3 Introduction to Probability

4.4 Mutually Exclusive Events

4.5 Conditional Probability

4.6 Independent Events and Unions of Events

4.7 Introduction to Random Variables and Probability Distributions

4.8 Mean and Standard Deviation of Random Variables

4.9 Combining Random Variables

UNIT 5: Sampling Distributions

5.1 Introducing Statistics: Why Is My Sample Not Like Yours?

5.2 The Normal Distribution, Revisited

5.3 The Central Limit Theorem

5.4 Biased and Unbiased Point Estimates

5.5 Sampling Distributions for Sample Proportions

5.6 Sampling Distributions for Differences in Sample Proportions

5.7 Sampling Distributions for Sample Means

5.8 Sampling Distributions for Differences in Sample Means

UNIT 6: Inference for Categorical Data: Proportions

6.1 Introducing Statistics: Why Be Normal?

6.2 Constructing a Confidence Interval for a Population Proportion

6.3 Justifying a Claim Based on a Confidence Interval for a Population Proportion

6.4 Setting Up a Test for a Population Proportion

6.5 Interpreting p-Values

6.6 Concluding a Test for a Population Proportion

6.7 Potential Errors When Performing Tests

6.8 Confidence Intervals for the Difference of Two Proportions

6.9 Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions

6.10 Setting Up a Test for the Difference of Two Population Proportions

6.11 Carrying Out a Test for the Difference of Two Population Proportions

UNIT 7: Inference for Quantitative Data: Means

7.1 Introducing Statistics: Should I Worry About Error?

7.2 Constructing a Confidence Interval for a Population Mean

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

7.4 Setting Up a Test for a Population Mean

7.5 Carrying Out a Test for a Population Mean

7.6 Confidence Intervals for the Difference of Two Means

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

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

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

7.10 Skills Focus: Selecting, Implementing, and Communicating Inference Procedures

UNIT 8: Inference for Categorical Data: Chi-Square

8.1 Introducing Statistics: Are My Results Unexpected?

8.2 Setting Up a Chi-Square Goodness of Fit Test

8.3 Carrying Out a Chi-Square Test for Goodness of Fit

8.4 Expected Counts in Two-Way Tables

8.5 Setting Up a Chi-Square Test for Homogeneity or Independence

8.6 Carrying Out a Chi-Square Test for Homogeneity or Independence

8.7 Skills Focus: Selecting an Appropriate Inference Procedure for Categorical Data

UNIT 9: Inference for Quantitative Data: Slopes

9.1 Introducing Statistics: Do Those Points Align?

9.2 Confidence Intervals for the Slope of a Regression Model

9.3 Justifying a Claim About the Slope of a Regression Model Based on a Confidence Interval

9.4 Setting Up a Test for the Slope of a Regression Model

9.5 Carrying Out a Test for the Slope of a Regression Model

9.6 Skills Focus: Selecting an Appropriate Inference Procedure

What’s more: https://www.youtube.com/watch?v=ls00h-IIinc&list=PL6334s8hsQG2wp7c5SGHcZM-i6gZy4krc