(b) Discuss why it is necessary to handle missing values. Use Python program to identify the variables with missing values in the given dataset. [No more than 200 words (including in-text citation, excluding Python code)] (15 marks)

In which of the following step the missing values are addressed ?  A. Data Cleaning  B. Data Collection  C. Data Arrangement  D. Data Gathering

Question 6According to the Module 2 reading, “Data Mining”, when data is missing in a systematic way, you should determine the impact of the missing data on the results and whether missing data can be excluded from what?1 pointThe studyThe data setThe analysisThe evaluation

Next, we need to check if the data contains any null values because missing values can disrupt the modelling process by causing errors or biases in our analysis.Write code that will check if our dataset contains any null values. If so, fill them with zero's. True or false. Our dataset contains no null values.Options:TrueFalse

Question 6According to the Module 2 reading, “Data Mining”, when data are missing in a systematic way, you can simply extrapolate the data or impute the missing data by filling in the average of the values around the missing data.1 pointFalse.True.

What is the significance of identifying and addressing missing data in a research dataset?  A. It has no impact on the analysis.  B. It helps in creating a more comprehensive dataset.  C. It makes the dataset smaller and more manageable.  D. It only affects qualitative data.