The World's Best Book Summaries
Why does big data offer more honest information? How can big data spark hope? In Everybody Lies, Seth Stephens-Davidowitz says that big data offers more honest information than we’ve ever had before. This information can be found through Google search results that reveal truths about humanity. Learn why Stephens-Davidowitz believes this information can be used for good, and why others say differently.
What is central tendency in statistics? What are the different ways to measure central tendency? Central tendency is a descriptive statistic that represents the middle of a data set. There are three main statistical measures of central tendency: the mean, median, and mode. Each of these measures describes a slightly different central position within a data set. Let’s examine the three statistical measures of central tendency.
What is recall bias in research methodology? Why is self-reporting unreliable as a data-collection method? Recall bias is a major problem in studies where data is collected through self-reporting. Because human memory is not like a tape recorder, our recollection of the past is unreliable. There are significant psychological influences on how a memory is recollected (e.g. the personal meaning we’ve assigned to the events). Keep reading to learn about recall bias.
What benefits does data science have that human intuition doesn’t? Why is data an extension of our intuition? In Everybody Lies, Seth Stephens-Davidowitz looks at the bigger picture of what big data is and why we should care about it. Though data science might seem arcane, Stephens-Davidowitz argues that it’s an extension of our natural intuition. Let’s look at the major benefits of data science that natural intuition doesn’t have.
What do people typically search on Google? What do a person’s Google searches say about them? Google searches and other internet activity reveal truths that might never come out in traditional data-gathering methods like surveys. In Everybody Lies, Seth Stephens-Davidowitz claims that people research topics that they would lie about in real life, such as sexuality, prejudice, and child abuse. Keep reading to learn what people search on Google and why they won’t discuss it in real life.
What is regression analysis in statistics? What can a regression test tell us about the relationship between two variables? Regression analysis is an inferential statistic that can help us infer relationships between variables that we wouldn’t otherwise be able to study. Regression analysis quantifies the direction, magnitude, and significance of an independent variable’s relationship to a dependent variable. Here’s a look at what inferential analysis does and the statistics involved.
What is program evaluation research? What types of program evaluations are there? Program evaluation refers to any situation where we’re interested in measuring the outcome of an event, which we refer to as a “treatment.” “Treatments” encompass academic interventions, social programs, political policies, fitness regimens, business tactics, clinical trials, and so on. Keep reading to learn about program evaluation research design and major challenges.
How do cause and effect studies benefit from big data? How does big data eliminate causal research problems? To get the most out of big data, Seth Stephens-Davidowitz says you should focus on its four benefits. In Everybody Lies, he dives into one of those benefits: easy cause-effect analysis. Let’s look at the two ways big data makes cause-and-effect studies easier.
How do people mislead with statistics? What are some real-world examples of misleading statistics? Anyone with the will and a capable computer program can perform statistical analyses. This accessibility combined with the ease and speed of information sharing in our technology-oriented culture makes it easy for misleading statistics to make their way into our lives and inform our opinions or decisions. Keep reading to find out how you can avoid falling into the trap of misleading statistics.
What is publication bias in research? Why do researchers choose not to report negative findings? Publication bias occurs when the outcome of a research project influences the decision to publish it. Researchers and publishers may be more inclined to share positive research findings because they make for more attention-grabbing headlines. Here’s how publication bias can lead to inflated confidence in research findings.