Descriptive and Inferential Statistics – A Comprehensive Guide For 2021
Introduction
A branch of mathematics, statistics, deals with the collection of data, its analysis and interpretation, and the ways of presenting numerical data. Statistics basically is a collection of data that is quantitative in nature. The subject of Statistics is broadly categorized as theoretical Statistics and Applied Statistics. Applied Statistics is further divided into descriptive statistics and inferential statistics. Let us understand what descriptive and inferential Statistics are and then delve down deeper to understand the differences between descriptive and inferential statistics.
1) What is descriptive statistics?
Descriptive Statistics is also referred to as samples and it determines multiple observations that you take through the research. It is defined as a finding group that fits the research parameters and the groups that are being tested and the use of graphs and stats to summarise the groups’ findings. In simple words, descriptive Statistics pairs the findings from a group and reduces them to simple and small major points. In the case of descriptive Statistics, you only test for the results that you get from the relevant individuals. It needs you to test continuously if the result affects a larger population portion.
Conclusions that can be measured with descriptive Statistics are through:
- The central tendency is the method of making use of the mean and the median to find the data location on the graph
- Dispersion is a way to find the division of the data points from the graph centre. If the number is small then this tells that the dispersion is close to the centre. A large number means that there is a larger space from the graphs’ epicentre.
- Skewness basically highlights the data point separation that you have measured. It lets you conclude if the data points are skewed or symmetrical from the measurements.
2) What is inferential statistics?
Inferential Statistics is where you take the data got from a sample and make predictions if that influences the findings on a larger population. You can make use of random sampling in order to evaluate the ways in which the different variables lead to making generalizations to do experiments. To make an accurate analysis you will have to find out the population that is being measured and creates a population sample. You then need to incorporate analysis in order to find out the sampling error.
Some ways in which inferential Statistics can be measured is through:
- Hypothesis test that determines if the population that is being measured has a high value as compared to the other data points in the analysis. It can also help to conclude if the population varies which is based on the results that you have earned from various experiments.
- The confidence interval discovers the error margin in the research and finds out if it affects the testing. You will have to estimate the population range and if it falls under the median or means calculation.
- Regression analysis is basically an association between the dependent and the independent variables of the experiment. You need to know the hypothesis test results in order to perform a regression analysis. This lets you know the relationship that is there between the subject matter. A few things that the regression analysis helps to test are the comparison between two sets of populations or maybe the comparison between height and weight of the different genders.
3) Difference between them
Here we list down the differences between descriptive and inferential statistics.
- The descriptive analysis gives information about the raw data that describes the data in a particular manner. The inferential analysis makes the inference about a population which is done using the data that is drawn from a population.
- Descriptive Statistics helps to organize, analyze, and present the data in a meaningful way. Inferential statistics allows comparing data and making predictions and hypotheses with it.
- Descriptive Statistics is used in order to describe a situation whereas inferential Statistics is used to explain the chances of the occurrence of an event
- Descriptive Statistics explains the data that is already known and is limited to a population or a sample of a small size. Inferential Statistics tries to reach out to a conclusion about the population.
- Descriptive Statistics can be done using graphs, charts, and tables. Inferential Statistics is achieved through probability.
- Descriptive Statistics has a tabular or diagrammatic representation of the final result whereas inferential Statistics represents the result in the probability form.
- Descriptive Statistics describes the situation where inferential Statistics explains the likelihood if the event will occur.
- Descriptive Statistics measures only the group that is assigned for the experiment which means that when you do the descriptive analysis you decide to not consider in the variables. In the case of inferential Statistics, you account for the sampling errors which may make you conduct additional tests that need to be on a large population depending on the amount of data that is required. In other words, you are likely to get a definite calculation when you use descriptive statistics.
- Since you are testing the variables using inferential Statistics it is easy to arrive at conclusions when you use descriptive statistics.
Conclusion
Statistics has a very important role to play in the research field. It helps to collect, analyze, and present the data in a form that is measurable. It is difficult to understand if the research lies in descriptive or inferential statistics. This is because people may not really be aware of these two Statistics branches. Descriptive statistics as the name suggests describes the population. On the contrary inferential Statistics is used in order to make a generalization of the population based on the sample. This shows that there is a lot of difference between descriptive and inferential Statistics which basically lies in what you do with the data.
Descriptive statistics is about how you illustrate the current data set whereas inferential stats focus on making an assumption about the extra population which is more than the state of data that is under study. Descriptive Statistics provides a summary of the data that the researcher has studied. Inferential Statistics, however, makes a generalization which is on the data that you have not studied actually. These are the differences between descriptive and inferential statistics.
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