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.

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

(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)

How does a researcher handle "Don't Know" responses during data preparation?  A. Exclude those responses from the analysis  B. Assign a neutral value to "Don't Know"  C. Treat them as missing data  D. Convert them to qualitative data

Which of the following statements accurately describe data? Select all that apply.1 pointThere are no limitations to data, as data measures are standard across users.Data can reveal important patterns, trends, and insights.Data is used to help organizations make more informed decisions.Data is a collection of facts.

2.Question 2 Fill in the missing word.All researchers commence their research with an issue or _________, investigate the relevant empirical evidence and literature to identify relevant research evidence which will help in designing the qualitative questions, collect data and analyse them. 0 / 1 pointSolutionProblem MethodsData set