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概率与统计概论I(4学分)

建议准备:m 111(m 241或m 251)或m 105或者至少安排数学20级

介绍概率和描述统计。包括图表和数据的关键阅读，基本概率论，随机变量，二项和正态概率分布。以中心极限定理为顶点。绘图计算器是必需的。推荐TI -83或TI -84。

MTH 243:概论与统计I

https://catalog.cocc.edu/course-outlines/mth-243/

成绩单标题Prob Stat 1学分4年级模式标准信件等级联系时数总计40授课时数40推荐准备MTH 111(适用于MTH 241或MTH 251)或MTH 105或至少安排数学20级。描述介绍概率和描述性统计。包括图表和数据的关键阅读，基本概率论，随机变量，二项和正态概率分布。以中心极限定理为顶点。绘图计算器是必需的。推荐TI -83或TI -84。学习成果1。学生将建模并解决来自一般、社会和管理科学的现实和理论线性规划问题;使用叙述、符号、图形和代数策略来设计、解决和解释模型。2. Student will model and solve real-world and theoretical problems from the general, social, and management sciences using counting theory and probability; narrative, symbolic, and algebraic strategies will be used to model and interpret solutions that use applications of permutations, combinations, the probability function, tree diagrams, and conditional probability models. 3. Student will analyze and describe real-world data sets using descriptive statistics for the general, social, and management sciences; narrative, graphical, and algebraic methods will be used to summarize and quantify data for the purpose of making informed decisions. 4. Student will understand, apply, solve, and interpret the standard forms of linear programming models when applied to specific applications from the general, social, and management sciences. 5. Student will use the graphing calculator to obtain numeric values for the measures of central tendency, measures of dispersion, and for graphical representations of statistical display. General education/Related instruction lists Science not Lab Mathematics

数学

https://catalog.cocc.edu/programs/mathematics/

学习数学可以培养分析和量化的能力，这在当今数据驱动的经济中是很有价值的。数学专业的学士学位是进入研究生院(如法学院、医学院、教育学院或商学院)以及在工业、政府、研究和商业中直接就业的很好的准备。此外，数学课程是许多相关科学、技术、工程和数学(STEM)项目的基础。

数学-艺术助理俄勒冈转学(AAOT)

https://catalog.cocc.edu/programs/mathematics/mathematics-aaot/

学习数学可以培养分析和量化的能力，这在当今数据驱动的经济中是很有价值的。俄勒冈州艺术学院转校的重点是数学，包括数学专业通常要求的课程，并满足俄勒冈州所有公立大学的低级别通识教育要求。

MTH 244:概论与统计学

https://catalog.cocc.edu/course-outlines/mth-244/

成绩单标题概论统计2学分4年级模式标准信年级联系学时总计40课学时40先决条件MTH 243介绍了推理统计分析的方法。包括置信区间、假设检验、线性相关和回归、卡方检验和方差分析(ANOVA)。可能包括非参数方法。使用电子表格和图形技术。学习成果1。在假设检验的背景下计算和解释置信区间。2.对涉及到平均数和比例的主张执行假设检验。3. Execute hypothesis tests with manual calculation and technology. 4. Perform quantitative and categorical tests of association. 5. Determine the proper statistical technique to use for various circumstances. 6. Produce and interpret statistical output from non-calculator statistical software. Content outline Central limit theorem Interval estimates Proportions Means Variance/standard deviation Bootstrap intervals One and two-sample hypothesis testing Correlation and regression Chi-squared tests Goodness of fit Independence/homogeneity One-way analysis of variance (ANOVA) Required materials No materials required. General education/Related instruction lists Mathematics