所以你想在大学里学习统计学。你需要选修什么课程?你不仅要上与统计学直接相关的课程,而且还要上与数学专业学生所上的课程类似(如果不相同)的课程。以下是一般构成统计学学士学位的核心课程的概述。不同院校对学位的要求不同,所以一定要查阅自己的学院或大学目录,以确定你需要拿什么才能毕业于统计学专业。微积分是许多其他数学领域的基础。典型的结石序列涉及至少三个疗程。这些课程如何划分信息有一些变化。微积分教授解决问题,发展数字能力,这两项技能对统计很重要。除此之外,微积分的知识对于证明统计结果是必要的。微积分一:在微积分序列的第一个课程中,你将学会仔细思考函数,探索诸如极限和连续性等主题。该类的主要焦点将转移到导数,该导数计算给定点处与图相切的线的斜率。在课程结束时,您将了解积分,这是一种计算具有奇怪形状的区域的区域。微积分二:在微积分序列的第二节课中,你将学到更多关于积分过程的知识。函数的积分通常很难计算它的导数,因此您将了解不同的策略和技术。本课程的另一个主要主题是无限序列和系列。本主题直观地检查了无限的数字列表,以及当我们试图将这些列表添加到一起时会发生什么。微积分三:微积分一和微积分二的基本假设是我们只处理一个变量的函数。在最有趣的应用中,现实生活要复杂得多。所以我们推广了我们已经知道的微积分,但是现在有多个变量。这导致结果不能再在图纸上描绘,而是需要三个(或更多)维度来举例说明。除了微积分序列之外,还有其他数学课程对统计学很重要。它们包括以下课程:线性代数:线性代数处理线性方程组的解,这意味着变量的最高幂是第一幂。虽然方程2x+3=7是线性方程,但是对线性代数最有兴趣的方程涉及多个变量。矩阵的主题被开发来解决这些方程。矩阵成为统计学和其他学科中存储数据的重要工具。线性代数也直接涉及统计学中的回归领域。概率:概率是许多统计的基础。它给我们一种量化机会事件的方法。从集合论开始定义基本概率,本课程将转向概率论的更高级主题,如条件概率和贝叶斯定理。其他主题的例子可以包括离散和连续随机变量、矩、概率分布、大数定律和中心极限定理。 实际分析:这门课程是对实数系统的仔细研究。除此之外,严格地发展了微积分中的极限和连续性等概念。微积分中很多定理都是没有证明的。在分析中,目的是用演绎逻辑证明这些定理。学习证明策略对于发展清晰的思维是很重要的。

新西兰怀卡托大学统计学Essay代写:线性代数

So you want to study statistics in college. What courses do you need to take? Not only do you take courses directly related to statistics, but you also take courses similar (if not different) to those taken by students majoring in mathematics. The following is an overview of the core courses that generally constitute the bachelor’s degree in statistics. Different colleges have different requirements for degrees, so you must consult your college or university catalogue to determine what you need to graduate in statistics. Calculus is the basis of many other fields of mathematics. A typical sequence of stones involves at least three courses of treatment. There are some changes in how these courses divide information. Calculus professors solve problems and develop numerical skills, which are important for statistics. In addition, the knowledge of calculus is necessary to prove the statistical results. Calculus 1: In the first course of calculus sequence, you will learn to think carefully about functions and explore topics such as limits and continuity. The main focus of this class will shift to the derivative, which calculates the slope of the line tangent to the graph at a given point. At the end of the course, you’ll learn about integrals, which are areas for calculating regions with strange shapes. Calculus II: In the second lesson of calculus sequence, you will learn more about the integral process. The integral of a function is usually difficult to calculate its derivatives, so you’ll understand different strategies and techniques. Another major theme of this course is Infinite Sequences and Series. This topic visually examines the infinite number lists and what happens when we try to add them together. Calculus 3: The basic assumption of Calculus 1 and Calculus 2 is that we only deal with functions of one variable. In the most interesting applications, real life is much more complex. So we generalize what we already know about calculus, but now there are many variables. As a result, the results can no longer be depicted on the drawing, but need three (or more) dimensions to illustrate. In addition to calculus sequences, there are other mathematics courses that are important for statistics. They include the following courses: linear algebra: linear algebra deals with the solution of a system of linear equations, which means that the highest power of a variable is the first power. Although equation 2x+3=7 is a linear equation, the equation most interested in linear algebra involves many variables. Matrix topics are developed to solve these equations. Matrix has become an important tool for data storage in statistics and other disciplines. Linear algebra is also directly related to the field of regression in statistics. Probability: Probability is the basis of many statistics. It gives us a way to quantify opportunistic events. Beginning with the definition of basic probability from set theory, this course will turn to more advanced topics of probability theory, such as conditional probability and Bayesian theorem. Examples of other topics may include discrete and continuous random variables, moments, probability distributions, laws of large numbers and central limit theorems. Practical analysis: This course is a careful study of the real number system. In addition, the concepts of limit and continuity in calculus are strictly developed. Many theorems in calculus have not been proved. In the analysis, the purpose is to prove these theorems with deductive logic. Learning proof strategies are important for developing clear thinking.

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