Subject – Data Analysis & Business Intelligence

Q1. Please read the below paragraph and write your opinion with any examples. References must.

Descriptive statistics represents properties of data using statistical calculations. Measures of central tendency such as mean, mode and range and measures of dispersion such as variance, standard deviation and range are used commonly. An example of descriptive statistics is calculating the average marks for students in a class for a subject.

Inferential statistics uses data from samples to make inferences about a population. The data is used to make conclusions, generalizations and predictions. An example is making conclusions about the performance of students in an entire country based on a sample selected.

Quantitative data are expressed as numbers and represent values. Examples are average salary, average area and average price. Qualitative data are expressed as categories and represent categories. Examples are profession, locality and target customers (Australian Bureau of Statistics, 2013).

Discrete variables are countable while Continuous variables are not. An example of a discrete variable is money in an account. An example of a continuous variable is time (Stephanie, 2018).

Q2. Please read the below paragraph and write your opinion with any examples. References must.

As a business analyst, learning descriptive and inferential statistics will enhance my decisions making process, provide the strong mathematical evidences and calculative analysis. Also, it will allow better data analysis and bigger picture view along with the more accuracy.

Descriptive statistics refers to the numerical measures that describes the attributes of a data set like average, mean, mode and median. Other measurements are skewness and kurtosis. (Besselaar, 2003). Inferential statistics refers to the numbers obtained by complex mathematical calculations in order to analyze the trends among larger number of populations, making decisions and predictions.  (Meletiou-mavrotheris, 2003).