Data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, and gain supporting evidence for decision making. They also construct models for predicting future trends from data. Data scientists need to know statistics because statistics plays a central role in the data science approach.
With the plethora of statistical tests, researchers are sometimes faced with the difficulty of choosing the appropriate test under the ideal condition.
In this discussion, describe a minimum of three statistical tests from the following list.
1. In your own words, describe the purpose of the statistical test.
2. Provide at least two examples of actual business analyst applications for each of the statistical tests identified. Use APA-style references wherever necessary to support your discussion.
Statistical Test
· Correlational
· Pearson correlation
· Spearman Correlation
· Chi-square
· Pair T-test
· Independent T-test
· ANOVA
· Simple Regression
· Multiple Regression
· Wilcoxon rank test
· Wilcoxon sum test
· Sign test
You must make at least two substantive responses to your classmates posts. Respond to these posts in any of the following ways:
· Build on something your classmate said.
· Explain why and how you see things differently.
· Ask a probing or clarifying question.
· Share an insight from having read your classmates postings.
· Offer and support an opinion.
· Validate an idea with your own experience.
· Expand on your classmates postings.
· Ask for evidence that supports the post
Discussion Length (word count): At least 250 words