Follow-up questions are an important part of Exploratory Data Analysis (EDA) because they help you drill down deeper into data patterns and uncover more insights. Here are some tips on how to use follow-up questions to guide your EDA: Start with general questions: Begin by asking broad questions about the dataset to get a general […]
Exploratory Data Analysis (EDA) is all about exploring a dataset to uncover patterns and insights. Here are some common questions to guide your EDA: What are typical values for the variables? This question helps you understand what the common or average values are for the variables in the dataset. For example, “What is the typical […]
Descriptive statistics are a way to summarize and describe the important features of a dataset. Here are some good questions to ask when exploring descriptive statistics: What is the range of the data? This question helps you understand how spread out the data is. For example, “What is the range of the temperatures in the […]
When exploring a dataset, one of the things you might want to investigate is how variables are related to each other. Here are some good questions to ask when exploring variable relationships or associations: Are there any patterns or trends in the data? For example, do higher temperatures lead to higher ice cream sales? Are […]
Exploratory Data Analysis (EDA) is all about using data to answer questions and uncover insights. But before you can start analyzing the data, it’s important to ask yourself: “Do I have the right data to answer this question?” Think of it like baking a cake. If you want to make a chocolate cake, you need […]
Data exploration is the process of analyzing and understanding a dataset to uncover insights and patterns. Asking questions is an essential part of this process, as it helps you focus your analysis and identify important aspects of the data. So, how can you use questions to guide data exploration? Let’s start with an analogy: asking questions […]
📊📈🔍 Hey guys, let’s talk about measures of variability! 📊📈🔍 When there are extreme values in a data set, measures that are less sensitive to those outliers are preferred. One such measure is the Interquartile Range (IQR), which looks at the difference between the first and third quartiles and ignores the minimum and maximum values. […]
Measures of dispersion, like standard deviation and interquartile range, give us information about how spread out the data is in a distribution. Measures of central tendency, like mean and median, give us information about where the center of the data is. Mean and Standard Deviation The mean and standard deviation are often used together because […]
The empirical rule is a way to estimate the spread of data in a normal distribution. It’s based on the idea that in a normal distribution, most of the data falls within a certain range of values around the mean. According to the empirical rule, in a normal distribution, approximately 68% of the data falls […]
📊📈🔍 Hey guys, let’s talk about measures of dispersion! 📊📈🔍 There are several measures of dispersion, including range, Interquartile Range (IQR), variance, standard deviation, and Mean Absolute Deviation (MAD). Here’s how to calculate each one: Range: Subtract the smallest value from the largest value. IQR: Subtract the first quartile from the third quartile. Variance: Calculate […]
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