Back to notes
Why is understanding errors in hypothesis testing important?
Press to flip
Understanding errors helps in evaluating the reliability of test results and in making informed decisions in data analysis.
What is the role of a Data Analyst compared to a Data Scientist?
A Data Analyst performs basic data interactions and reporting, while a Data Scientist engages in sophisticated data analysis and model building.
What is the focus of calculus in data science?
Differentiation and integration are the primary focuses of calculus in data science.
Explain Inferential Statistics and its significance.
Inferential Statistics makes predictions or inferences about a population based on a sample, involving estimation and hypothesis testing.
Name the measures of central tendency and what they provide.
Mean, Median, Mode: They provide summaries of data's central value.
What are Descriptive Statistics, and what do they include?
Descriptive Statistics involve summarizing data using measures like central tendency (mean, median, mode) and dispersion (variance, standard deviation, range).
What is the difference between Null Hypothesis (H0) and Alternative Hypothesis (H1)?
Null Hypothesis (H0) is the initial assumption in hypothesis testing, whereas the Alternative Hypothesis (H1) is what you aim to prove.
How is calculus applied in data science?
It is used in optimizing algorithms and understanding dynamic changes through differentiation and integration.
What is the importance of Linear Algebra in data science?
Linear Algebra is crucial for understanding matrices, vectors, and optimization, which are fundamental in algorithms and predictive analytics.
What are the two types of errors in hypothesis testing?
Type I Error (α): Rejecting a true null hypothesis, Type II Error (β): Failing to reject a false null hypothesis
What roles fall under 'others' in the categories of data professionals?
MLOps Engineer, Data Engineer, Machine Learning Manager, AI Manager
In hypothesis testing, when is a Z-test used over a T-test?
Z-Test is used when sample size > 30 and population standard deviation is known; T-Test is used when sample size < 30 or population standard deviation is unknown.
Describe the main focus of Business Analysts in data roles.
Business Analysts focus on extracting insights to solve business problems and require interaction with stakeholders.
What are the four main categories of math critical for data professionals?
Statistics, Linear Algebra, Calculus, Discrete Mathematics
What topics are covered under Discrete Mathematics crucial for data professionals?
Combinatorics, Graph Theory, Probability Theory
Previous
Next