# How to Write a Statistics Paper

Statistics is a science that involves the collection, analysis, and presentation of data. Statistical analysis, therefore, is the analysis of the data samples collected and using them to represent the whole population. Statistics papers mainly have 4 basic components; statement of the problem, research design, data analysis, and conclusion.

The ultimate trick to writing an excellent statistics paper is knowing what the research questions to be addressed are and working on gathering and analyzing available data in a bid to answer them.

## Here are the steps on how to write a statistics paper:

### 1. Overview of your topic

The first step in writing your statistics paper is analyzing and writing an overview of your topic. This dictates several things in your research, that is, why your topic is worth studying, what the appropriate research data to use is i.e. whether primary or secondary data, and how you will go about conducting your research. For example; your topic could be does eating sugary foods daily lead to being overweight?

For the above topic, analyzing it allows you as the statistics researcher to know what variables are in play and how to go about corroborating or disagreeing with the statement that eating sugary foods leads to being overweight. The importance of analyzing your topic before you begin writing your paper is also to know what the requirements of the paper will be. For example, does your paper call for information analysis, presentation of information, persuasion of the readers, or is it more about problem-solving? These questions will give direction to your paper.

### 2. Write the hypothesis

Hypotheses are ideas or predictions that the statistical analysis will test or analyze. Formulating the hypothesis statements to be used is the first step in your research. What forms the hypothesis are the variables you will undertake in your research. There are two types of variables; independent and dependent variables. Dependent variables depend on other factors, while independent variables can stand on their own.

For the topic we had chosen above, sugary foods here are an independent variable while being overweight is the dependent variable. An example of a hypothesis you could use for this topic is; that the number of sugary foods consumed daily lead to being overweight. There are different types of hypotheses. The main ones used are null and alternative hypotheses.

For our example, the null hypothesis would be:

- There is no relationship between eating sugary foods daily and being overweight.

The alternative hypothesis would be:

- Eating sugary foods daily is positively correlated with being overweight.

### 3. Formulate your research design

Research design is the strategy you will use to show the correlation between the variables you have chosen for your paper. Formulating your research design will determine how you will collect and analyze the data that is relevant to your research. It determines the statistical tests that you will use to test your formulated hypothesis.

The research design chosen should be neutral, reliable, and valid. It sets out the techniques to be used, the method of analysis applied, the types of research methodology to be used, any objections to the research, and the timeline that the research will take. It also states any controls that affect the dependent variable of the research.

### 4. Data collection

Your chosen research topic determines the data set that will be used. There are statistics research questions that may require the use of primary data, i.e. for the researcher to collect the data personally, or secondary data, i.e. for the researcher to use already available data. It can be very expensive and tedious to collect primary data, hence most research papers are based on secondary data. Where you are permitted to use secondary data, choose materials that will work best for your paper.

It is important to know that most researchers use sample data to act as a representative of the whole population. As long as the sampling procedures employed when choosing the sample are appropriate, statistical analysis allows for the sample’s findings to represent the whole population. Note that when the sample used is too small, it may be too unrepresentative, and if the sample is too large, it may be expensive and tedious. For that reason, a sufficient sample size should be correctly calculated. The different methods of data collection include surveys, interviews, questionnaires, and focus groups, among others.

### 5. Inspect your data

The process of inspecting the collected data involves organization, displaying, and visualization. Data analysis is the most important aspect of your paper, even more so than the data collection step. Organizing the data involves the use of tables to distinguish the various sets of data collected. Displaying of data involves using the dependent and independent variables of your study to create a bar chart.

Visualizing the data would be showing the relationship between the dependent and independent variables by use of, say, a scatter plot. It focuses on statistical and mathematical analysis of the data sets to demonstrate the topic of research that was being discussed. It helps determine whether the data collected answers the research questions initially posed by the topic.

### 6. Test your hypothesis

In statistics, hypothesis testing involves testing whether the data collected in the research sufficiently supports the hypothesis stated at the beginning. It uses the collected data samples to make conclusions on the whole population to whom the hypothesis is related. Hypothesis testing involves determining the null hypothesis, which we had stated earlier, and then choosing what kind of test to perform which determines whether to accept or reject the null hypothesis.

The hypothesis test that you choose to use will highly depend on the type of data used in your research. Your test will show how the two variables of your research relate and whether they support your hypothesis. Based on the statistical outcome, you may reject or fail to reject the null hypothesis previously stated. It is important to note that you never fail or reject the alternate hypothesis. The reason is, that testing the alternate hypothesis is not meant to prove or disprove anything.

### 7. Interpret your results

Interpreting your results is the final step in your research. It involves showing whether the findings of your research confirm the findings of other research works previously done by other scholars. The interpretation of your results is one of the most important parts of your research. For qualitative research findings, organize your results around the themes of your research, whereas, for quantitative research, you should organize your findings around your hypotheses.

This section of your research involves relating your findings to the findings of previous research works to confirm whether the results align or not. Whether your findings corroborate or contradict previous studies, make sure to indicate explanations for why that may be. This section of your research should tie back to the problem stated at the beginning of your paper.

### 8. Write the final copy of your paper

Once you have completed data collection, analysis, and interpretation, then you can write the final copy. A statistics paper takes the form of other research papers. You have to have an introduction, body, conclusion, and references. The main difference between a common research paper and a statistics paper is the content in the body. Ensure that your thesis statement is bold and that your introduction is broad and convincing. As with other papers, your introduction sets the tone for your paper. It tells the reader what to expect.

Your body should contain your findings, i.e. the hypotheses statements, research design, data collection methods, the data collected, and the interpretation of the collected data. Remember that a statistics research paper intends to demonstrate your competence in applying statistics to your given topic. The conclusion for your paper should include the importance of your research topic, any research gaps noted in your study, and reiterate the findings of your data analysis.