Last Attempt DA0-001 Questions

The table provided shows an inconsistency in the ‘Gender’ column, which lists three distinct values: Male, Female, and College. This is inconsistent because ‘College’ is not a gender category. The ‘Gender’ column should only have two distinct values, typically ‘Male’ and ‘Female’, to accurately represent gender data. This error could be due to a data entry mistake or a misclassification during data collection.

In data analysis, it’s crucial to ensure that categorical variables like gender are consistent and correctly classified, as this can significantly impact the analysis results. Data cleaning processes often involve identifying and correcting such inconsistencies to maintain the integrity of the data set.

This is because exploratory data analysis is a type of process that performs initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization, such as box plots, histograms, scatter plots, etc. Exploratory data analysis can be used to understand and summarize the data, as well as to generate hypotheses or questions for further analysis or research. For example, exploratory data analysis can be used to identify and visualize the characteristics, features, or behaviors of the data, as well as to measure their distribution, frequency, or correlation. The other options are not types of processes that perform initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization. Here is what they mean:

A t-test is a type of statistical method that tests whether there is a significant difference between the means of two groups or samples, such as whether there is a difference between the average exam scores of two classes in this case. A t-test can be used to test or verify a claim or an assumption about the data, as well as to measure the confidence or the error of the estimation.

A performance analysis is a type of process that measures whether the data meets certain goals or objectives, such as targets, benchmarks, or standards. A performance analysis can be used to identify and visualize the gaps, deviations, or variations in the data, as well as to measure the efficiency, effectiveness, or quality of the outcomes. For example, a performance analysis can be used to determine if there is a gap between a student’s test score and their expected score based on their previous performance.

A link analysis is a type of process that determines whether the data is connected to other datapoints, such as entities, events, or relationships. A link analysis can be used to identify and visualize the patterns, networks, or associations among the datapoints, as well as to measure the strength, direction, or frequency of the connections. For example, a link analysis can be used to determine if there is a connection between a customer’s purchase history and their loyalty program status.

A CSV file is a type of flat file that stores data as plain text in a table-like structure with rows and columns. Each row represents a single record, while columns represent fields or attributes of the data. A CSV file uses commas or other delimiters to separate the values in each row. A CSV file can be easily imported or exported by various applications and programs12