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Introduction to Discrete & Continuous Probability Distributions

  ✅ 1. What is a Probability Distribution? A probability distribution describes how probabilities are distributed over the values of a random variable . Random Variable : A variable whose values are outcomes of a random phenomenon. 🧮 2. Types of Probability Distributions Type Description GIS Example Discrete           Takes countable values  Number of landslides per year in a          valley Continuous          Takes infinite values over an                 interval Rainfall (mm), elevation, temperature  📌 Discrete Probability Distributions 🎯 3. Binomial Distribution ✅ Definition : Used when an experiment is repeated n times , and each trial has two outcomes : success or failure. ✅ Conditions : Fixed number of trials (n) Only two possible outcomes per trial (success/failure) Constant probability of success (p) Trials are in...

Bar Graph

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  A bar graph , also known as a bar chart, is a visual representation of data using rectangular bars of varying lengths. It is commonly used to compare and display categorical or discrete data, where each category or group is represented by a separate bar. Creating a Bar Graph: To create a bar graph, follow these steps: Identify the data: Determine the data you want to represent in the bar graph. This data should be categorical or discrete, such as different categories, groups, or time periods. Choose the axes : Decide which variable you want to represent on the x-axis (horizontal axis) and which variable you want to represent on the y-axis (vertical axis). The x-axis typically represents the categories or groups, while the y-axis represents the values or frequencies associated with each category. Determine the scale : Determine the appropriate scale for each axis. The scale should allow for a clear and meaningful representation...

Mode

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 In statistics, mode refers to the value or values in a dataset that appears most frequently. It is a measure of central tendency, along with the mean and median. Here are examples of modes for ungrouped and grouped data: Ungrouped data : Consider the following set of numbers: 3, 4, 2, 1, 4, 5, 4, 6, 2. The mode is the value that appears most frequently, which in this case is 4. Therefore, the mode for this dataset is 4. Grouped data : Suppose we have a dataset that represents the number of hours spent watching TV per week for a group of people, and the data is grouped into the following frequency distribution: Hours per week Number of people 0-4 10 5-9 15 10-14 5 15-19 3 To find the mode for this dataset, we need to determine which group has the highest frequency. In this case, the group with the highest frequency is 5-9. N...

Median

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The median is another measure of central tendency that represents the middle value of a data set. To find the median, the data set is arranged in order from lowest to highest (or highest to lowest), and then the middle value is selected. If the data set has an even number of values, then the median is the average of the two middle values. For ungrouped data , the formula for finding the median is: If n is odd: Median = (n + 1) / 2 th value If n is even: Median = (n / 2) th value + ((n / 2) + 1) th value) / 2 where n represents the number of values in the data set. Example of median for ungrouped data: Consider the following set of data: 5, 6, 3, 8, 7 First, we arrange the data set in order: 3, 5, 6, 7, 8 Since the number of values in the data set is odd (n = 5), the median is the middle value, which is 6. For grouped data , the formula for finding the median is: Median = L + ((n/2 - F) / f) * h where L represents the lower limit of the median class interval, n represents the total n...

Arithmetic Mean

  The arithmetic mean, also known as the average, is a measure of central tendency that represents the typical or average value of a set of data. It is calculated by adding up all the values in a data set and dividing the total by the number of values. The formula for the arithmetic mean for a data set with n values is: x̄ = (x₁ + x₂ + ... + xn) / n where x̄ represents the arithmetic mean, and x₁, x₂, ..., xn represent the individual values in the data set. For ungrouped data , the formula for the arithmetic mean is simply the sum of all the values in the data set divided by the number of values. Example of arithmetic mean for ungrouped data: Consider the following set of data: 5, 6, 3, 8, 7 The arithmetic mean is: x̄ = (5 + 6 + 3 + 8 + 7) / 5 = 29 / 5 = 5.8 For grouped data , the formula for the arithmetic mean is: x̄ = ∑ (fi * xi) / ∑ fi where x̄ represents the arithmetic mean, fi represents the frequency of each class interval, and xi represents the midpoint of each class inter...