Inductive Reasoning: Everything You Need to Know When Assessing Inductive Reasoning Skills

Inductive Reasoning

Inductive reasoning is a type of logical reasoning that involves drawing general conclusions from specific observations. It is the opposite of deductive reasoning, which involves drawing specific conclusions from general principles.

Inductive reasoning is often used in science, where scientists make observations and collect data to develop theories and hypotheses. For example, a scientist might observe that all swans they have ever seen are white. Based on this observation, they might conclude that all swans are white. This is an inductive conclusion, because it is based on a limited number of observations.

Inductive reasoning is also used in everyday life. For example, if you always get a wet umbrella when you go outside without checking the forecast, you might conclude that it is going to rain. This is an inductive conclusion, because it is based on your past experiences.

How Does Inductive Reasoning Work?

Inductive reasoning is based on the assumption that the future will be similar to the past. In other words, if we have observed something to be true in the past, we can assume that it will be true in the future.

Of course, this is not always the case. Just because all swans we have ever seen are white does not mean that all swans are white. There could be a black swan out there somewhere. However, inductive reasoning is still a useful tool for making predictions and decisions.

Types of Inductive Reasoning

There are two main types of inductive reasoning:

Strong induction: Strong induction is a type of inductive reasoning that is based on a large number of observations and that is very likely to be true. For example, the scientist who concluded that all swans are white after observing a large number of white swans used strong induction.
Weak induction: Weak induction is a type of inductive reasoning that is based on a small number of observations or that is less likely to be true. For example, the person who concluded that it was going to rain after getting a wet umbrella once used weak induction.

Discover How To Get Started Assessing Inductive Reasoning Skills

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How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)

We get a high flow of applicants, which leads to potentially longer lead times, causing delays in the pipelines which can lead to missing out on good candidates. Alooba supports both speed and quality. The speed to return to candidates gives us a competitive advantage. Alooba provides a higher level of confidence in the people coming through the pipeline with less time spent interviewing unqualified candidates.

Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)