Statistics Archives

Why Thinking in Probabilities Is Not Intuitive

Do you take into account probability when making decisions? Why do we make decisions that contradict probabilistic logic? Understanding probability can be especially relevant to our daily lives because we make decisions based on our perception of probability all the time. However, our perception of likely outcomes is often mathematically irrational. This is because thinking in probabilities isn’t intuitive: Most people think in terms of binary categories of “yes,” “no,” and “maybe.” Here’s why we make decisions that contradict probabilistic logic.

What Is Inferential Analysis in Statistics?

What is inferential analysis? What can inferential statistics tell us about data? In simple terms, inferential statistics are a kind of combination of data and probability. Just as probability is never a guarantee of an outcome, there are no definitive answers in inferential statistics. Rather, inferential statistics help us use what we do know to make math-based best guesses about what we want to know. Keep reading for the ultimate guide to inferential statistics.

The Correlation Coefficient: Statistics 101

What is the correlation coefficient in statistics? What can the correlation coefficient tell us about the relationship between two variables? What is the danger in mistaking correlation for causation? A figure called the correlation coefficient quantifies the strength and direction of the relationship between two variables. A common mistake in statistics is equating correlation with causation. It can be tempting to extrapolate beyond a correlation coefficient, but that will lead to causal conclusions that correlation can’t support. In this article, we’ll break down the concept of statistical correlation and explain why correlation does not equal causation.

Healthy-User Bias in Medical Research

What is healthy-user bias? How can we isolate whether an intervention actually accounts for differences between individuals? Healthy-user bias occurs in studies that aim to assess the effect of a certain treatment or intervention. Because the people who choose to partake in such studies tend to be significantly different from their peers, it’s difficult to assess the degree to which the intervention (and not the participants’ characteristics) accounts for the findings. Keep reading to learn about healthy-user bias and how it affects research findings.

The Difference Between Correlation & Causation

What’s the difference between correlation and causation? What are the consequences of mistaking correlation for causation? Just because two variables are correlated doesn’t mean one is causing the other. Correlation quantifies a relationship between two variables, but it doesn’t explain that relationship. This is a crucial distinction to keep in mind, as equating correlation and causation can lead to misinformed decisions. Here’s why correlation does not imply causation.

Survivorship Bias in Statistics Skews Results

What is survivorship bias in statistics? How does survivorship bias skew our interpretation of the research findings? Any time a portion of a study sample is able to “leave” the study, we should be wary of survivorship bias. Survivorship bias occurs when we draw conclusions based on the “survivors” of a certain treatment or intervention. Keep reading to learn about survivorship bias and how it affects research findings.

The R^2 Statistic in Linear Regression

What is the R2 statistic? What does the value of R2 tell us about the change in the dependent variable? The R2 statistic represents the proportion of the variance in the dependent variable that stems from the change in the independent variable. When using the R2 statistic to quantify the association between independent and dependent variables, it’s important to keep in mind that the R2 in linear regression only applies to linear relationships. It’s possible for two variables to be related, just not in a linear way. Here’s a look at the R2 statistic in linear regression.

What Is Selection Bias in Research?—Explained

What is selection bias in research methodology? How does selection bias affect research findings? Selection bias occurs when individuals chosen to partake in a study are not representative of the population of interest. Selection bias can be subtle—if researchers aren’t cognizant of selection bias when developing data collection methods, the fact that a sample is not truly random might go unnoticed. Here’s why it’s important to watch out for selection bias when collecting data for the purposes of research.

How Is Social Science Data Collected? Big Data!

How can we use big data to study social science? How does data give us more insight into the social sciences? Through search data, researchers can discover psychological and sociological information that traditional surveys couldn’t provide. Seth Stephens-Davidowitz, the author of Everybody Lies, uses Freud’s theories of sexuality as an example. Read how to receive social science data with the help of big data.

How Big Data Provides New Information

What types of information does big data provide? How does it get this information? In Everybody Lies, Seth Stephens-Davidowitz says big data opens our eyes to new types of information that weren’t previously available. We can find this new information from search engines and unconventional data sources. Keep reading to learn where this big data information comes from.