what is statistics？谈到统计学，很多同学其实只有一个模糊的概念。百度百科对于统计学这样描述：统计学是通过搜索、整理、分析数据等手段，以达到推断所测对象的本质，甚至预测对象未来的一门综合性科学。其中用到了大量的数学及其它学科的专业知识，它的使用范围几乎覆盖了社会科学和自然科学的各个领域。而很多人认为统计学只是在体育方面的统计，或者只是停留在大学的初步认识当中。如今，统计学的技术被运用到多种领域，本文将帮您进入统计学的世界，了解一些统计数据流程和主要内容。留学生统计学作业代写，请联系Meeloun论文网客服！
Everyday we encounter information. Information comes at us in a number of different ways and in different forms. How many calories did each of us eat for breakfast? How far from home did everyone travel today? How big is the place that we call home? How many other peoplecall it home? And that’s only the beginning of the information that is outthere. To make sense of all of this information, certain tools and ways of thinking are necessary. The mathematical science called statistics is whathelps us to deal with this information overload.
Statisticsis the study of numerical information, called data. Statisticians acquire,organize, and analyze data. Each part of this process is also scrutinized. The techniques of statistics are applied to a multitude of other areas of knowledge. Below is an introduction to some of the main topics throughout statistics.
Populations and Samples
One ofthe recurring themes of statistics is that we are able to say something about alarge group based upon the study of a relatively small portion of that group.The group as a whole is known as the population. The portion of the group that we study is the sample.
As an example of this, suppose we wanted to know the average height of people living in the United States. We could try to measure over 300million people, but this would be infeasible. It would be a logistical night mare conduct the measurements in such a way that no one was missed and noone was counted twice.
Due tothe impossible nature of measuring everyone in the United States, we couldinstead use statistics. Rather than finding the heights of everyone in the population, we take astatistical sample ofa few thousand. If we have sampled the population correctly, then the averageheight of the sample will be very close to the average height of the population.
To draw good conclusions, we need good data to work with. Theway that we sample a population to obtain this data should always bescrutinized. Which kind of sample we use depends on what question we’re asking about the population. The most commonly used samples are:
It’s equally important to know how the measurement of the sampleis conducted. To go back to the above example, how do we acquire the heights of those in our sample?
·Do we let people report their own height on a question naire?
·Do several researchers throughout the country measure different people and report their results?
·Does a single researcher measure everyone in the sample with the same tape measure?
Each of these ways of obtaining the data hasits advantages and drawbacks. Anyone using the data from this study would wantto know how it was obtained
Organizing the Data
Sometimes there is a multitude of data, and we can literally get lost in all of the details. It’s hard to see the forest for the trees. That’s why it’s important to keep our data well organized. Careful organization and graphical displays of the data help us to spot patternsand trends, before we actually do any calculations.
Since The way that we graphically present our data depends upona variety of factors. Common graphs are:
·Pie charts or circle graphs
·Bar or pareto graphs
·Stem and leaf plots
·Box and whisker graphs
In addition to these well known graphs, there are others that are used in specialized situations.
One way to an alyze data is called descriptive statistics. Here the goal is to calculate quantities that describe our data. Numbers called the mean, median andmodeareall used to indicate theaverageorcenter of the data. The range andstandard deviationare used to say how spread out the data is. More complicated techniques, such ascorrelationand regression describe data that is paired.
what is statistics？statistics作业代写，留学生统计学作业代写？联系网站客服吧！
When webegin with a sample and then try to infer something about the population, weare usinginferentia lstatistics. In working with this area of statistics, the topic ofhypo the sistestin garises. Here we see the scientific nature of the subject of statistics, as we state a hypothesis, then use statistical tools with oursample to determine the likelihood that we need to reject the hypothesis ornot. This explanation is really just scratching the surface of this very usefulpart of statistics.
Applications of Statistics
It is no exaggeration to say that the tools of statistics areused by nearly every field of scientific research. Here are a few areas thatrely heavily on statistics:
The Foundations of Statistics
Although some think of statistics as a branch of mathematics, itis better to think of it as a discipline that is founded upon mathematics.Specifically, statistics is built up from the field of mathematics known a sprobability. Probability gives us a way to determine how likely an event is tooccur. It also gives us a way to talk about randomness. This is key tostatistics because the typical sample needs to be randomly selected from the population.
Probabilitywas first studied in the 1700s by mathematicians such as Pascal and Fermat. The1700s also marked the beginning of statistics. Statistics continued to growfrom its probability roots, and really took off in the 1800s. Today it’stheoretical scope continues to be enlarged in what is known as mathematical statistics.
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