AP Statistics

1.1 Introducing Statistics: What Can We Learn from Data? · ⁨統計学入門：データから何を学べるか？⁩ 1.2 The Language of Variation: Variables · ⁨変動の言語：変数⁩ 1.3 Representing a Categorical Variable with Tables · ⁨カテゴリー型変数を表で表現する⁩ 1.4 Representing a Categorical Variable with Graphs · ⁨グラフによるカテゴリカル変数の表現⁩ 1.5 Representing a Quantitative Variable with Graphs · ⁨グラフによる定量的変数の表現⁩ 1.6 Describing the Distribution of a Quantitative Variable · ⁨定量的変数の分布の説明⁩ 1.7 Summary Statistics for a Quantitative Variable · ⁨定量的変数の要約統計量⁩ 1.8 Graphical Representations of Summary Statistics · ⁨要約統計量の視覚的表現⁩ 1.9 Comparing Distributions of a Quantitative Variable · ⁨定量変数の分布の比較⁩ 1.10 The Normal Distribution · ⁨正規分布⁩

2.1 Introducing Statistics: Are Variables Related? · ⁨統計学入門：変数間に関連はあるか？⁩ 2.2 Representing Two Categorical Variables · ⁨二つのカテゴリー変数の可視化⁩ 2.3 Statistics for Two Categorical Variables · ⁨二つのカテゴリー変数のための統計⁩ 2.4 Representing the Relationship Between Two Quantitative Variables · ⁨二つの定量変数間の関係の可視化⁩ 2.5 Correlation · ⁨相関⁩ 2.6 Linear Regression Models · ⁨線形回帰モデル⁩ 2.7 Residuals · ⁨残差⁩ 2.8 Least Squares Regression · ⁨最小二乗回帰⁩ 2.9 Analyzing Departures from Linearity · ⁨線形からの逸脱の分析⁩

3.1 Introducing Statistics: Do the Data We Collected Tell the Truth? · ⁨統計学入門：収集したデータは真実を語っているか？⁩ 3.2 Introduction to Planning a Study · ⁨研究計画立案への入門⁩ 3.3 Random Sampling and Data Collection · ⁨無作為抽出とデータ収集⁩ 3.4 Potential Problems with Sampling · ⁨抽出に関する潜在的な問題⁩ 3.5 Introduction to Experimental Design · ⁨実験設計への入門⁩ 3.6 Selecting an Experimental Design · ⁨実験設計の選定⁩ 3.7 Inference and Experiments · ⁨推論と実験⁩

4.1 Introducing Statistics: Random and Non-Random Patterns? · ⁨統計学入門：ランダムかつ非ランダムのパターンか？⁩ 4.2 Estimating Probabilities Using Simulation · ⁨シミュレーションを用いた確率の推定⁩ 4.3 Introduction to Probability · ⁨確率への導入⁩ 4.4 Mutually Exclusive Events · ⁨排反事象（Mutually Exclusive Events）⁩ 4.5 Conditional Probability · ⁨条件付き確率（Conditional Probability）⁩ 4.6 Independent Events and Unions of Events · ⁨独立事象および事象の和集合⁩ 4.7 Introduction to Random Variables and Probability Distributions · ⁨確率変数と確率分布への入門⁩ 4.8 Mean and Standard Deviation of Random Variables · ⁨確率変数の平均と標準偏差⁩ 4.9 Combining Random Variables · ⁨確率変数の結合（Combining Random Variables）⁩ 4.10 Introduction to the Binomial Distribution · ⁨二項分布への入門⁩ 4.11 Parameters for a Binomial Distribution · ⁨二項分布のパラメータ⁩ 4.12 The Geometric Distribution · ⁨幾何分布⁩

5.1 Introducing Statistics: Why Is My Sample Not Like Yours? · ⁨統計学入門：なぜ私の標本はあなたのもの似ていないのか？⁩ 5.2 The Normal Distribution, Revisited · ⁨正規分布、再訪⁩ 5.3 The Central Limit Theorem · ⁨中心極限定理⁩ 5.4 Biased and Unbiased Point Estimates · ⁨バイアス付きおよびバイアスなしの点推定量⁩ 5.5 Sampling Distributions for Sample Proportions · ⁨標本比率のための標本分布⁩ 5.6 Sampling Distributions for Differences in Sample Proportions · ⁨標本比率の差のための標本分布⁩ 5.7 Sampling Distributions for Sample Means · ⁨標本平均のための標本分布⁩ 5.8 Sampling Distributions for Differences in Sample Means · ⁨標本平均の差のための標本分布⁩

6.1 Introducing Statistics: Why Be Normal? · ⁨統計学入門：なぜ正規分布なのか？⁩ 6.2 Constructing a Confidence Interval for a Population Proportion · ⁨母比率のための信頼区間の構築⁩ 6.3 Justifying a Claim Based on a Confidence Interval for a Population Proportion · ⁨母比率の信頼区間に基づく主張の正当化⁩ 6.4 Setting Up a Test for a Population Proportion · ⁨母比率のための検定の設定⁩ 6.5 Interpreting p-Values · ⁨p値の解釈⁩ 6.6 Concluding a Test for a Population Proportion · ⁨母比率のための検定の結論付け⁩ 6.7 Potential Errors When Performing Tests · ⁨検定実行時の潜在的な誤り⁩ 6.8 Confidence Intervals for the Difference of Two Proportions · ⁨二つの比率の差のための信頼区間⁩ 6.9 Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions · ⁨母比率の差の信頼区間に基づく主張の正当化⁩ 6.10 Setting Up a Test for the Difference of Two Population Proportions · ⁨二つの母比率の差のための検定の設定⁩ 6.11 Carrying Out a Test for the Difference of Two Population Proportions · ⁨二つの母比率の差のための検定の実行⁩

7.1 Introducing Statistics: Should I Worry About Error? · ⁨統計学入門：誤りを心配すべきか？⁩ 7.2 Constructing a Confidence Interval for a Population Mean · ⁨母平均のための信頼区間の構築⁩ 7.3 Justifying a Claim About a Population Mean Based on a Confidence Interval · ⁨信頼区間に基づく母平均に関する主張の正当化⁩ 7.4 Setting Up a Test for a Population Mean · ⁨母平均のための検定の設定⁩ 7.5 Carrying Out a Test for a Population Mean · ⁨母平均のための検定の実行⁩ 7.6 Confidence Intervals for the Difference of Two Means · ⁨二つの平均値の差のための信頼区間⁩ 7.7 Justifying a Claim About the Difference of Two Means Based on a Confidence Interval · ⁨信頼区間に基づく二つの平均値の差に関する主張の正当化⁩ 7.8 Setting Up a Test for the Difference of Two Population Means · ⁨二つの母平均値の差のための検定の設定⁩ 7.9 Carrying Out a Test for the Difference of Two Population Means · ⁨二つの母平均値の差のための検定の実行⁩ 7.10 Skills Focus: Selecting, Implementing, and Communicating Inference Procedures · ⁨スキル・フォーカス：推論手続の選定、実施、および伝達⁩

8.1 Introducing Statistics: Are My Results Unexpected? · ⁨統計学入門：結果が予期せぬものか？⁩ 8.2 Setting Up a Chi-Square Goodness of Fit Test · ⁨カイ二乗適合度検定の設定⁩ 8.3 Carrying Out a Chi-Square Test for Goodness of Fit · ⁨カイ二乗適合度検定の実行⁩ 8.4 Expected Counts in Two-Way Tables · ⁨交差表における期待されるカウント数⁩ 8.5 Setting Up a Chi-Square Test for Homogeneity or Independence · ⁨カイ二乗同質性または独立性検定の設定⁩ 8.6 Carrying Out a Chi-Square Test for Homogeneity or Independence · ⁨カイ二乗同質性または独立性検定の実行⁩ 8.7 Skills Focus: Selecting an Appropriate Inference Procedure for Categorical Data · ⁨スキル・フォーカス：カテゴリーデータに適した推論手続の選定⁩

9.1 Introducing Statistics: Do Those Points Align? · ⁨統計学入門：その点は一直線上にあるか？⁩ 9.2 Confidence Intervals for the Slope of a Regression Model · ⁨回帰モデルの傾きのための信頼区間⁩ 9.3 Justifying a Claim About the Slope of a Regression Model Based on a Confidence Interval · ⁨信頼区間に基づく回帰モデルの傾きに関する主張の正当化⁩ 9.4 Setting Up a Test for the Slope of a Regression Model · ⁨回帰モデルの傾きのための検定の設定⁩ 9.5 Carrying Out a Test for the Slope of a Regression Model · ⁨回帰モデルの傾きのための検定の実行⁩ 9.6 Skills Focus: Selecting an Appropriate Inference Procedure · ⁨スキル・フォーカス：適切な推論手続の選定⁩