Introduction Flashcards

(25 cards)

1
Q

What is data analysis used for?

A
  1. Answer questions
  2. Suggest conclusions
  3. Support decision making
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2
Q

What is the process of Data Analysis?

A

Converting raw data into useful information via statistical and logical methods

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3
Q

What are independent vs dependent variables?

A
  1. Independent variables are model inputs
  2. Dependent variables are model outputs
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4
Q

How are outputs derived?

A

With respect to potential relationships with inputs

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5
Q

What tasks fall under a Data Analyst? ( 3 )

A
  1. KPI tracking and Performance Benchmarking
  2. Reporting Automation and Dashboard Creation
  3. Business, market and industry analysis
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6
Q

What tasks fall under Data Science? ( 3 )

A
  1. Machine learning and predictive modeling
  2. Statistical Analysis
  3. Algorithm Optimisation
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7
Q

What are the components of the data ecosystem? ( 5 )

A
  1. Sources
  2. Identification
  3. Transformation
  4. Analysis and visualization
  5. Governance and security
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8
Q

List out the steps of Data Lifecycle ( 8 )

A
  1. Generation
  2. Collection
  3. Processing
  4. Storage
  5. Management
  6. Analysis
  7. Visualization
  8. Interpretation
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9
Q

What does Processing in Data Lifecycle ensures?

A
  1. Raw data is processed and manipulated to be usable and consitent
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10
Q

Where does Data is being stored?

A
  1. Databases
  2. Data Warehouses
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11
Q

What is does Visualization in Data Lifecycle ensures?

A
  1. Insights are presented in graphical or visual formats for easier interpretation
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12
Q

How are Data being Interpreted in Data Lifecycle?

A
  1. Results are interpreted to inform decision-making and drive actions
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13
Q

What does Management in Data Lifecycles ensures?

A
  1. Data is organized, maintained, and governed to ensure quality and accessibility
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14
Q

What is a hypothesis?

A

A statement predicting a relationship between two or more variables for scientific testing

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15
Q

What is the null hypothesis?

A

Statement that elevated AI usage does not affect critical thinking

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16
Q

What is the alternative hypothesis?

A

Statement that elevated AI usage negatively affects critical thinking

17
Q

What is the difference between qualitative and quantitative variables?

A

Qualitative variables describe categories; quantitative variables measure numeric values

18
Q

What are four variable types?

A
  1. Continuous
  2. Discrete
  3. Ordinal
  4. Nominal
19
Q

What are the three main analytics types? ( 3 )

A
  1. Descriptive
  2. Predictive
  3. Diagnostic
20
Q

List out the steps by Analytical Process ( 5 )

A
  1. Data Import and Exploration
  2. Preliminary Data Analysis
  3. Data Exploration and Visualisation
  4. Data Wrangling
  5. Predictive Analytics
21
Q

What are key preliminary steps in R?

22
Q

What is exploratory data analysis (EDA)?

A

Creative multivariate plots to explore interactions and generate insights from information

23
Q

What is data wrangling? ( 2 )

A

Cleaning data and feature engineering
1. Handling unusual or anomalous information
2. Creating new features from existing information

24
Q

What is the Tidyverse?

A

A collection of R packages for data science tasks

25
What is predictive analytics?
Using models to forecast outcomes based on data patterns