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Hypothesis testing is a technique used to determine whether an assumption about the population is true. Null hypothesis and alternate hypothesis are two types of hypotheses that you may hear when conducting this type of test. Having a good understanding about null and alternate hypothesis will help you better design good hypothesis tests and understand their results in a nice manner. It is very important for data scientists to be able to distinguish between null and alternate hypothesis and design hypothesis tests. In this blog post, we will understand the definition and examples of the null and alternate hypothesis.
What are different scenarios for hypothesis testing?The following are two different scenarios for hypothesis testing:
What is the null and alternate hypothesis?Hypothesis can be categorized in two different types:
How to formulate null and alternate hypothesis?Here is the technique which can be used for formulating null and alternate hypothesis:
What are some examples of null and alternate hypothesis?The following are some examples of null and alternate hypothesis:
In this blog post, we learned about the definition and examples of Null and Alternate Hypothesis. Null hypothesis represents the default state or well-established belief in a particular claim while alternate hypothesis is typically against what is believed as true. For example, buy stocks during down market would have no impact on returns would be null hypothesis. The technique used to formulate Null and Alternate Hypotheses involves identifying whether there is a new claim being made about something which has been established as truth or if someone wants to question existing beliefs and make new claim altogether. If you wanted to learn more, feel free to drop a comment and I will try and address your queries. You may also want to check a related post – Hypothesis testing explained with examples.
I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking Ajitesh KumarI have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. For latest updates and blogs, follow us on Twitter. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking Posted in Data Science. Tagged with Data Science. What is an example of a null hypothesis and alternative hypothesis?Null Hypothesis: On the average, the dosage sold under this brand is 50 mg (population mean dosage = 50 mg). Alternative Hypothesis: On the average, the dosage sold under this brand is not 50 mg (population mean dosage ≠ 50 mg). This is a two-sided alternative hypothesis.
How would you write the null and alternative hypotheses?Null hypothesis (H0): There's no effect in the population. Alternative hypothesis (Ha or H1): There's an effect in the population.
How do you write a null hypothesis?To write a null hypothesis, first start by asking a question. Rephrase that question in a form that assumes no relationship between the variables. In other words, assume a treatment has no effect. Write your hypothesis in a way that reflects this.
How do you write an alternative hypothesis example?The alternate hypothesis is just an alternative to the null. For example, if your null is “I'm going to win up to $1,000” then your alternate is “I'm going to win $1,000 or more.” Basically, you're looking at whether there's enough change (with the alternate hypothesis) to be able to reject the null hypothesis.
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