Statistics is one of the most important uses of any organization. With the application ranging from business models, market reports, weather forecasts, scientific calculations, engineering applications, etc. Statistics can be defined as the collection, organizing, analyzing, interpreting, and presenting the data and getting the result that can be understood by general people. Statistics are generally used when there is a lot of data which will takes days to go through so by the use of statistics the data are produced in various types of graphs which can be understood easily. In the early days, statistics was considered to be just the part of mathematics but nowadays it is considered to be a distinct mathematical science. It has become increasingly important for many organizations to hire some experts in statistics for their growth and ease in dealing with a large pool of data that the company gathers. For example, the census of any country generates a lot of data that can be understood to make some assumptions which can take a lot of time if not dealt with statistics first. It is said to be statistics is one of the most important parts of modern mathematical studies which makes it one of the important subjects for any branches of studies. Statistics are generally taught to students from high school till master's degree programs.

Statistics is not all about the processing of data but it also has certain ways that how the data is collected and is then filtered. For any statistical method to get the accurate answer it is very necessary to define the criteria in which the data is collected and is filtered. The survey, points on which the data has to be collected, etc. are also predefined for any data that has to be presented using statistics. The two of the main methods used in statistics are:

As the name suggests this method is used when the data are known and these data have to just analyze and presented to the audience. This method is applicable only if all the data for the statistics is already known and no data is missing for the part which has to be presented. Descriptive Statistics can be further divided into two parts depending on the variables. These are:

**Univariate analysis:**This analysis tends to represent the data that has to be presented for only one variable. The mean, median, mode, range, quartiles, variance, standard deviation, skewness, kurtosis, etc. The distribution of the variable may be showed using a variety of graphs like histograms, stem and leaf displays, etc.**Multivariate analysis:**This analysis tends to represent data that has to be presented for two or more variables. This type of analysis not only represents the data but also gives the relation between the two variables. It is used more in scientific calculations.

It is used for finding the underlying distributive properties from the data analysis done on the data. It is usually done to test the various hypothesis and properties and usually can be used to find the estimates for the future. It is fairly useful to find the values that may occur in the future from the data of the previous time. This method is usually used in conjunction with the probability to get fairly accurate results.

Students find it extremely difficult to complete the assignments given in statistics because of the vast knowledge they have to know before they may be able to complete their assignments. Also, it is difficult to find the proper data set required to complete the assignment. For students to complete the assignment correctly they should know how to manipulate the data to get the desired results. Also, students should know the various methods that can be used to get the data analyzed properly and accurately. Students often spend a lot of time analyzing the data and they usually get the wrong answer due to the various mistakes they have done. Students don’t have the necessary experience for making a flawless report from the results they get. These all lead to a reduction of their marks which leads to low grades in their examination. This can lead to low job opportunities for students. To reduce these effects, we at Assignment Hippo provide online statistics assignment help for students who are unable to do their assignments correctly or are unable to do their assignments because of time constraints. Students often don’t have time because of the many subjects they have to study and make assignments on. This is the main reason why many students skip some of the subjects like statistics to compensate for the time they need for other subjects. We help students to get the assignments and projects completed, along with the report which generally comes with these problems. Also, our experts choose the correct types of the graph to visualize the data which makes the professors praise the students. These all help the student to get good marks in their examination and hence get a good and stable job of their liking. Now we should know what makes us the best among the other online assignment providers.

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Case Problem Information A case consists of analyzing a large data set that you analyze using the techniques that are developed in the course. It should be a multivariable data set (at least three measures for each “subject’). The intent of this assignment is to “bring together” course concepts and demonstrate that you have an understanding of appropriate analysis for given data. You may work on a case as an individual, or you may collaborate with other class members as a team. It is your choice, and the choice has no effect on the grade. If you choose to collaborate, only one team member will submit the case; just be sure to include the names of all participants on the submission. Note that if you decide dissolve collaborative efforts, you are free to do so; each member can submit a separate project. You do not have to notify me. Proceed considering the following. 1. Identify your case early in the semester. The data set should have an n of at least 50 (more is better) and must include at least three variables. Many data sets are available in the text or you may use one of your choosing. Cases are identified at the end of Chapters. Refer to Chapter 17 for information regarding factors for consideration in analyzing data. 2. Throughout the semester, complete an analysis of the data. Use Excel to complete the analysis. • Include the descriptive analysis of the data. Describe the data using appropriate graphs/charts and appropriate descriptive measures. Include at least two graphs/tables that involves the relationship between two or more variables. Be sure that graphs, charts are appropriate, labeled and formatted properly. Include an interpretation of the information. See the various examples on the web site. Note that the format of the graph and table is important – an important part of statistics is communicating information is a clear manner • Include appropriate inferential methods to analyze the data (such as those in Chapters 8-11, 13 and 16. Note that use only the methods that are appropriate for your data. (You don’t have to use all of them.) Be sure to include the assumptions, an interpretation of the analysis and clearly stated summary information/conclusions. Note: a grading rubric is included at the end of this document. Specifically, the final report should include the following sections. 1. Section 1 Introduction/Background Information. • Define the problem, giving basic background information. • State the research questions – specifically, what are you investigating? • Include a list of the variables that were measured and their units of measure. • Reference the source of your data; if original, briefly state how it was collected. 2. Section 2 Descriptive Analysis. • Include appropriate charts, graphs, and descriptive measures. Pay attention to the format and be sure you have a clear/good format. (Some examples are posted to the web site.) Review the document on Principles of Graph Construction. Include a meaningful title for each graph and each table. Label the axes. Format the numerical values – round the numbers considering the precision of the original data. Interpret the graph in terms of the data. • For descriptive measures: Define the measure. Interpret the measure in terms of the data. 3. Section 3 Inferential Analysis/ statistical test(s). • State the statistical test/procedures that are used. • State the test assumptions and discuss the implications for your analysis. • State the null & alternate hypotheses – both formally & informally – for each test. • Present the results. See the text and/or posted examples for the format 4. Section 4 Conclusions Summarize/interpret the results. At the end of the semester, submit your results in one Excel document. Be sure that it is a clearly labeled and formatted spreadsheet. Be sure that the procedures for the analysis are clearly presented. The deadline is posted on the course schedule. Evaluation of the Cases Refer to the following rubric when developing your case for submission. Example of the type of rubric that is used in grading the case Be sure to reference the source of your data.

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