Learn Statistics

  In statistics, there are four types of measurement scales: nominal, ordinal, interval, and ratio. Each of these scales has different properties and uses, and they are often used to describe and analyze different types of data. 1. Nominal Scale : The nominal scale is the simplest measurement scale and is used to categorize data into distinct groups or categories. Examples of nominal data include gender, ethnicity, religion, and marital status. Nominal data can only be described in terms of frequencies and percentages, and mathematical operations such as addition, subtraction, and division cannot be performed on this type of data. 2. Ordinal Scale: The ordinal scale is used to measure data that can be ranked or ordered in some way. For example, a Likert scale that measures agreement or disagreement with a statement is an ordinal scale. The scale is ordered from strongly agree to strongly disagree. In this case, the numerical values assigned to each response indicate the order of...

 Discrete and continuous variables are two types of variables used in statistics and mathematics. A discrete variable is a type of variable that can only take on specific, separate values. These values are usually countable and often represent whole numbers. For example, the number of students in a classroom, the number of cars sold in a day, or the number of pets in a household are all examples of discrete variables. Discrete variables are usually represented using a histogram or a bar graph . A continuous variable is a type of variable that can take on any value within a certain range or interval. These values are usually measured and can be infinitely subdivided. For example, height, weight, temperature, and time are all examples of continuous variables. Continuous variables are usually represented using a line graph or a scatter plot. One key difference between discrete and continuous variables is that it is often possible to find the exact value of a continuous variable...

There are two types of data quantitative and  qualitative. As the word tells,  quantitative is about a number such as 5, 8, or 12, numerical data is quantitative data. There are two types of numerical data discrete and continuous  data. Discrete data is based on counting while  continuous  data is based on measurement. A whole number is assigned to discrete data and a real number is assigned to continuous data. Counting the number of cats will be discrete data while measuring the distance from one point to another will be continuous data. Both continuous and discrete data are quantitative data because both are numerical. The difference is observed by counting while the other is measured .  Now we will come to qualitative data. Qualitative data is based on observation and you use words to describe this data not numbers. Qualitative data is basically descriptive data based on observation and words to describe the data not numbers and this is the key di...

The first step of every statistical analysis you will perform is to determine whether the  data you are dealing with is a population or a sample. A population is the collection of all items of interest to our study and is usually denoted  with an uppercase N. The numbers we’ve obtained when using a population are called parameters.  A sample is a subset of the population and is denoted with a lowercase n, and the numbers  we’ve obtained when working with a sample are called statistics.  Now you know why the field we are studying is called statistics 😊 Let’s say we want to make a survey of the job prospects of the students studying in  the New York University.  What is the population?  You can simply walk into New York University and find every student, right?  Well, probably, that would not be the population of NYU students.  The population of interest includes not only the students on campus but also the ones at  home, on exchang...

  Statistics is  the science of collecting, organizing,  analyzing, and interpreting data. It is all  about data. First, we collect  data. Data just doesn't appear, we  collect it through surveys, experiment, or measuring and recording the information. Once we get the data then we organize it and put it in order either ascending or descending order. This is the most common thing to be applied to data. The data can be put in table form or can be represented in graphical form. To check what the data tells us, we analyze the data. We find the mean, median, mode, range, or standard deviation of the data. So  what statistics is all about it is  all about collecting data and using  it to help answer a question. S o statistics is all about answering a  question.   Now what exactly is a  good statistical question, well a  statistical question is where you expect  to get a variety of answers that is really big a variety of an...