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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Mining | 25% | - Given a scenario, execute techniques for data manipulation - Explain data acquisition concepts - Explain common techniques for data manipulation and optimization - Identify common reasons for cleansing and profiling datasets |
| Topic 2: Data Governance, Quality, and Controls | 14% | - Explain key aspects of data quality - Compare and contrast types of data controls - Summarize important data governance concepts |
| Topic 3: Data Concepts and Environments | 15% | - Compare and contrast common data structures and file formats - Identify basic concepts of data schemas and dimensions - Compare and contrast different data types |
| Topic 4: Data Analysis | 23% | - Summarize types of analysis and key analysis techniques - Given a scenario, apply the appropriate descriptive statistical methods - Explain the purpose of inferential statistical methods |
| Topic 5: Visualization | 23% | - Given a scenario, apply the appropriate type of visualization - Given a scenario, use appropriate methods for dashboard development - Explain important aspects of a report that tell a data story - Compare and contrast types of reports - Given a scenario, translate business requirements to support data-driven decisions |
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NEW QUESTION # 322
A customer survey reveals 90% positive feedback. Which of the following statistical methods would be best to utilize to determine the reliability of a data set and predict how a larger sample of customers over the same time period might respond?
Answer: B
Explanation:
A low standard deviation in survey responses indicates that the data points tend to be close to the mean, suggesting a high level of consistency among the responses. This consistency is crucial for determining the reliability of the data set and predicting future outcomes. If the standard deviation is low, it means that the positive feedback is not only high but also consistent, making it a reliable indicator of customer satisfaction and a good predictor of how a larger sample might respond.
NEW QUESTION # 323
Given the below:
Which of the following numbers represents a Type I error?
Answer: D
NEW QUESTION # 324
Which of the following statistical methods requires two or more categorical variables?
Answer: D
Explanation:
Explanation
This is because a chi-squared test is a type of statistical method that tests the association or independence between two or more categorical variables, such as gender, race, or occupation. A chi-squared test can be used to compare the observed frequencies of the categories with the expected frequencies under the null hypothesis of no association or independence. For example, a chi-squared test can be used to determine if there is a relationship between smoking and lung cancer. The other statistical methods do not require two or more categorical variables. Here is why:
Simple linear regression is a type of statistical method that models the relationship between a continuous dependent variable and a continuous or categorical independent variable, such as height, weight, or education level. A simple linear regression can be used to estimate the slope and intercept of the best-fitting line that describes how the dependent variable changes with the independent variable. For example, a simple linear regression can be used to predict the weight of a person based on their height.
Z-test is a type of statistical method that tests the significance of the difference between a sample mean and a population mean, or between two sample means, when the population standard deviation or the sample sizes are large enough. A z-test can be used to compare the average scores of two groups of students on a standardized test.
Two-sample t-test is a type of statistical method that tests the significance of the difference between two sample means when the population standard deviation is unknown or the sample sizes are small. A two-sample t-test can be used to compare the average salaries of two groups of employees in different departments.
NEW QUESTION # 325
Given the customer table below:
Which of the following chart types is the most appropriate to represent the average spending of active customers vs. inactive customers?
Answer: A
Explanation:
A Pie chart is the most suitable for representing the average spending of active customers versus inactive customers. Pie charts are effective for comparing parts of a whole, which makes them ideal for visually displaying the proportion of spend between two distinct groups. They are widely used to depict percentage distributions and are straightforward, allowing immediate analysis of the active vs. inactive customer spending distribution at a glance.
NEW QUESTION # 326
An analyst in a consumer bank department wants to showcase the concentration of accounts opened in the United States by ZIP Code to describe the effectiveness of the bank's marketing campaigns. Which of the following would be the best way to visualize the data?
Answer: C
NEW QUESTION # 327
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