Cognitive biases

1. Cognitive biases

Hi, welcome to this video where we'll delve into cognitive biases.

2. Beyond data collection bias

While data bias often originates in the data collection phase, it can also manifest in other stages of the data lifecycle, including analysis, model development and interpretation. This will be our focus in this chapter. One prevalent type of bias at these lifecycle stages is cognitive biases, which are systematic patterns of deviation from norm or rationality in judgment. Let’s dive into the common cognitive bias types in more detail.

3. Confirmation bias

The most common type is confirmation bias. It refers to the tendency to seek, interpret, and remember information in a way that confirms pre-existing beliefs or hypotheses, while disregarding contradictory evidence. In data analysis, confirmation bias can lead to favoring information that aligns with our initial assumptions. This potentially distorts the interpretation of results and hinders the discovery of novel insights. For instance, a marketing manager analyzing customer feedback may pay more attention to positive comments about a new product while overlooking negative feedback that challenges their belief in its success.

4. Overconfidence bias

Overconfidence bias refers to the tendency to overestimate one's own abilities, knowledge, or judgments. In the context of data analysis, this bias can lead analysts to be overly confident in the accuracy or reliability of their findings, potentially overlooking errors or uncertainties in the data or analysis process.

5. Recency bias

Recency bias is the tendency to give more weight or importance to recent events or information when making judgments or decisions. In data analysis, recency bias can lead analysts to prioritize recent data points or trends over historical data, potentially overlooking long-term patterns or trends that may be relevant to the analysis.

6. Memory bias

Our memories are also susceptible to bias, influencing the way we recall information. It refers to the ways in which our memories can be distorted or influenced by various factors, leading us to recall information inaccurately. A sales manager reviewing past sales performance may remember successful outcomes more vividly, attributing them to effective strategies, while downplaying or forgetting instances where similar tactics failed.

7. Availability heuristic

The availability heuristic is a mental shortcut that relies on immediate examples that come to a person's mind when making judgments or decisions. For example, a risk analyst may overestimate the likelihood of a rare event, such as a data breach, if recent news headlines have highlighted similar incidents, leading to biased risk assessments.

8. Anchoring bias

Lastly, anchoring bias is another common type that occurs when individuals rely too heavily on initial information, the "anchor", when making decisions or estimations. For example, if an analyst starts with an initial estimate of a parameter, they may unconsciously adjust their subsequent estimates or interpretations around that initial anchor, even if it's incorrect or misleading.

9. The feedback loop of cognitive biases

Cognitive biases can significantly influence decision-making, problem-solving, and interpersonal relationships. They create patterns of selective perception, interpretation, and memory recall, leading to a reinforcement of existing beliefs and perspectives. This reinforcement often creates a feedback loop, where individuals consistently encounter information that aligns with their views, further solidifying their beliefs over time. It leads to closed-mindedness and a resistance to considering alternative perspectives.

10. Let's practice!

Now that you have learned about the essential elements of cognitive biases, let's put that knowledge into practice!

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