Descriptive and Predictive. Describe each one. How are they different? How do they work together? Why are they both necessary? What is the biggest difference between the two?
Descriptive helps to describe the characteristics of a population with the help of tables, calculation or graphs whereas, Predictive helps us to make inferences about a population. It helps in Predicting about a population on the basis of the sample taken from the same population.
So, descriptive helps to describe the sample population using mean, standard deviation, making a bar chart or describing the shape of the normal probability curve. Predictive are used for two purposes:
1) to estimate parameters, i.e. taking a statistics from the sample population and using it to say or make a prediction about the population parameter.
2) To test hypotheses. In order to answer research questions, Predictive statistics is important. One can use the sample data to test and answer various research questions using inferential statistics. T-distributions, regression analysis, ANOVA, MANOVA etc are some examples of inferential statistics.
The main difference between Predictive and descriptive is that descriptive statistics describes the population using a sample data, whereas, Predictive statistics helps in drawing conclusion about a population using a sample data.
The way how descriptive statistics and inferential statistics are complementary is that descriptive statistics helps to present the raw data in an accurate way, while Predictive statistics makes inferences from a data sample and helps in generalizing it to a bigger population. Both, Predictive and descriptive statistics are very important to research.
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