日本語 English
| 開講年度/ Academic YearAcademic Year |
20232023 |
| 科目設置学部/ CollegeCollege |
全学共通科目・全学共通カリキュラム（総合系）/University-wide Liberal Arts Courses (Comprehensive Courses)University-wide Liberal Arts Courses (Comprehensive Courses) |
| 科目コード等/ Course CodeCourse Code |
多彩な学び/主題別/多彩な学び/主題別多彩な学び/主題別 |
| テーマ・サブタイトル等/ Theme・SubtitleTheme・Subtitle |
社会を読み解く方法を学ぶ |
| 授業形態/ Class FormatClass Format |
オンデマンド（全回オンデマンド）/On-demand (all classes are on-demand)On-demand (all classes are on-demand) |
| 授業形態（補足事項）/ Class Format (Supplementary Items)Class Format (Supplementary Items) |
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| 授業形式/ Class StyleCampus |
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| 校地/ CampusCampus |
池袋/IkebukuroIkebukuro |
| 学期/ SemesterSemester |
秋学期他/Fall OthersFall Others |
| 曜日時限・教室/ DayPeriod・RoomDayPeriod・Room |
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| 単位/ CreditCredit |
22 |
| 科目ナンバリング/ Course NumberCourse Number |
CMP2200 |
| 使用言語/ LanguageLanguage |
日本語/JapaneseJapanese |
| 履修登録方法/ Class Registration MethodClass Registration Method |
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| 配当年次/ Grade (Year) RequiredGrade (Year) Required |
配当年次は開講学部のR Guideに掲載している科目表で確認してください。配当年次は開講学部のR Guideに掲載している科目表で確認してください。 |
| 先修規定/ prerequisite regulationsprerequisite regulations |
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| 他学部履修可否/ Acceptance of Other CollegesAcceptance of Other Colleges |
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| 履修中止可否/ course cancellationcourse cancellation |
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| オンライン授業60単位制限対象科目/ Online Classes Subject to 60-Credit Upper LimitOnline Classes Subject to 60-Credit Upper Limit |
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| 学位授与方針との関連/ Relationship with Degree PolicyRelationship with Degree Policy |
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| 備考/ NotesNotes |
オンデマンド授業 |
| テキスト用コード/ Text CodeText Code |
FB143 |
Students will think about society, position social survey data analysis as a tool to solve problems, and learn methods for using data to test inferences and hypotheses.
Students will learn about the basic statistical knowledge needed for statistical data aggregation and analysis. From among descriptive statistics and inference statistics, the curriculum will be developed with an emphasis on inference statistics. Students will acquire the basic idea of inference statistics based on probability theory, and will learn basic statistics such as mean value, median, mode, variance, and standard deviation; indices that indicate the strength of the relationship between variables such as covariance and correlation coefficient; chi-square tests for cross-table related indices and independence; single regression analysis; control of partial correlation coefficients and confounding variables; and multiple regression analysis. In addition, students will learn about test theory such as t-test and analysis of variance. Students will learn the applied contents of statistics, and learn topics from analysis methods for dealing with univariates and bivariates to some analysis methods for dealing with three variables that are the entry point to multivariate analysis.
※Please refer to Japanese Page for details including evaluations, textbooks and others.
社会について考え，課題を解決する道具として社会調査データ分析を位置づけ，データを用いて推論や仮説を検証するための手法を体得する。
Students will think about society, position social survey data analysis as a tool to solve problems, and learn methods for using data to test inferences and hypotheses.
統計的データの集計・分析に必要な，基礎的な統計知識について学ぶ。記述統計学と推測統計学のうち，主に推測統計学に重点を置いたカリキュラムを展開する。確率論に基づいた推測統計学の基本的な考え方を身につけ，平均値や中央値，最頻値や分散，標準偏差といった基本統計量，共分散や相関係数といった変数間の関連性の強さを表す指標，クロス表の関連指標と独立性についてのカイ二乗検定，単回帰分析，偏相関係数と交絡変数の統制，重回帰分析などについて学ぶ。また，t検定や分散分析といった検定論についても学習する。統計学の応用的な内容を学習し，1変量，2変量を扱った分析手法から，多変量解析の入り口となる3変数を扱った分析手法についても一部学習する。
Students will learn about the basic statistical knowledge needed for statistical data aggregation and analysis. From among descriptive statistics and inference statistics, the curriculum will be developed with an emphasis on inference statistics. Students will acquire the basic idea of inference statistics based on probability theory, and will learn basic statistics such as mean value, median, mode, variance, and standard deviation; indices that indicate the strength of the relationship between variables such as covariance and correlation coefficient; chi-square tests for cross-table related indices and independence; single regression analysis; control of partial correlation coefficients and confounding variables; and multiple regression analysis. In addition, students will learn about test theory such as t-test and analysis of variance. Students will learn the applied contents of statistics, and learn topics from analysis methods for dealing with univariates and bivariates to some analysis methods for dealing with three variables that are the entry point to multivariate analysis.
| 1 | 記述統計学と推測統計学 |
| 2 | 標本抽出（1） |
| 3 | 確率の基礎と確率分布 |
| 4 | 標本抽出（2） |
| 5 | 推定 |
| 6 | 推定：平均の推定 |
| 7 | 推定：比率の推定 |
| 8 | 統計的検定の基礎論理（1） |
| 9 | 母平均の差の検定、t検定 |
| 10 | 分散分析 |
| 11 | カイ二乗検定 |
| 12 | 三重クロス表の分析 |
| 13 | 相関と回帰 |
| 14 | 因果への挑戦 |
板書 /Writing on the Board
スライド（パワーポイント等）の使用 /Slides (PowerPoint, etc.)
上記以外の視聴覚教材の使用 /Audiovisual Materials Other than Those Listed Above
個人発表 /Individual Presentations
グループ発表 /Group Presentations
ディスカッション・ディベート /Discussion/Debate
実技・実習・実験 /Practicum/Experiments/Practical Training
学内の教室外施設の利用 /Use of On-Campus Facilities Outside the Classroom
校外実習・フィールドワーク /Field Work
上記いずれも用いない予定 /None of the above
授業時間外の学習に関する指示は、必要に応じて別途指示する。
| 種類 (Kind) | 割合 (%) | 基準 (Criteria) |
|---|---|---|
| 平常点 (In-class Points) | 100 |
コース教材内の練習問題(15%) 課題(課題(1)と課題(2)の計2回）(30%) 特別課題（特別課題Aと特別課題Bの計2回）(55%) |
| 備考 (Notes) | ||
| その他 (Others) | |||||
|---|---|---|---|---|---|
| オンラインで提示する内容がテキストに相当する。 |
| その他 (Others) | |||||
|---|---|---|---|---|---|
| コース教材内で適宜指定する場合がある。 |
履修許可者は，授業1週目にはCanvas LMSにログインして、内容を確認すること。