PSY 179 Critical Thinking in Psychology PDF

17.12.2024 PSY 179- Critical thinking in Psychology Critical Thinking in Everyday Life Today Critical thinking in everyday life...

17.12.2024 PSY 179- Critical thinking in Psychology Critical Thinking in Everyday Life Today Critical thinking in everyday life 1  17.12.2024 Critical thinking in everyday life Critical thinking helps us analyze situations logically, avoid fallacies, and make well-reasoned decisions. It enhances our ability to solve problems creatively and adapt to challenges effectively. It helps in critically evaluating news sources, media content, and understanding underlying biases. Why we need to think critically in the information age Overwhelming amount of data: We are constantly exposed to a flood of data. Knowing how to discern reliable information is crucial. Rise of misinformation: Inaccurate information spreads faster than ever, making critical thinking more important. Need for independent judgment: Developing independent, rational thinking helps navigate complex issues without relying solely on unreliable sources. 2  17.12.2024 How instant information leads Speed of information sharing: to misinformation Social media and news cycles move faster than fast-checking can Understanding the dynamics keep up with. of information flow Confirmation bias: People tend to share information that supports their beliefs, regardless of its accuracy. Echo chambers: Algorithm-driven platforms create environments where misinformation is reinforced by like-minded individuals. Group dynamics and critical thinking Recognize groupthink: Understand how group pressure can lead to conformity, often suppressing critical and independent thinking. Encourage diverse perspectives: Embrace diverse opinions to challenge assumptions and improve the quality of group decisions. Practice independent analysis: Reflect on your own beliefs and question whether they are influenced by the group, or genuinely yours. 3  17.12.2024 Understanding research in media Evaluating media claims and statistics Identify misleading information: Recognize selection bias, correlation vs causation errors, and misleading visual representations in the media. Assess credibility of sources: Evaluate the reliability of news outlets, authors, and any cited research using critical questions. Understand statistical manipulations: Be attentive of data manipulation through skewed graphs or statistical misrepresentation to sway opinions. Media literacy: Navigating fake news and real news Analyze the source: Check whether the information source is trustworthy by evaluating its reputation and editorial standards. Look for emotional manipulation: Fake news often aims to evoke strong emotions. Be cautious of headlines designed to provoke fear, anger, or excitement. Cross-check information: Verify the information by checking multiple reputable sources to confirm its accuracy. 4  17.12.2024 Evaluating numbers What is plausibility? Determining the realistic nature of information Initial sanity check: Assess whether a given claim is even possible based on basic understanding and common sense. Data sources: Evaluate the credibility and reliability of the sources behind the claim. Comparative analysis: Compare data against similar know values to verify if the claim holds plausibility. 5  17.12.2024 What would you do with this claim? Is it plausible? In the thirty-five years since marijuana laws stopped being enforced in California, the number of marijuana smokers has doubled every year. Let’s assume there was only one marijuana smoker in California 35 years ago, (It’s a very conservative estimate, there were half a million marijuana arrests nationwide in 1982). and double that number every year for 35 years It would yield more than 17 billion- larger than the population of the entire world!! Try it yourself and you’ll see that doubling every year for twenty-one years gets you to over a million: 1; 2; 4; 8; 16; 32; 64; 128; 256; 512; 1024; 2048; 4096; 8192; 16,384; 32,768; 65,536; 131,072; 262,144; 524,288; 1,048,576 What would you do with this claim? Is it plausible? Our best salesperson made 1,000 sales a day. How fast can you dial a phone number yourself? Probably 5 seconds? What if you allow another 5 seconds for the phone to ring? Now, what happens if we assume that every call ends in a sale—is this a realistic scenario, or are we giving every advantage just to see if the claim works? Estimate at least 10 seconds for making a successful pitch, followed by another 40 seconds to collect the buyer's credit card details and address. What’s the duration of one call? 5+5+10+40= 60 seconds!! So you can make only 60 sales in an hour, or 480 sales in a very busy 8 hour shift with no pause!! 6  17.12.2024 Let’s evaluate this pie chart First rule of pie charts: The percentages have to add up to 100. Apparently, voters could indicate support for multiple candidates. However, the results should not be displayed using a pie chart. Types of Mean: The arithmetic average, calculated by averages: Mean, adding all values and dividing by the number of values. median and mode Median: The middle values in a set of numbers, providing a better measure when data is Understanding skewed. how averages Mode: The value that appears most frequently in a dataset, often used in categorical data. (You can be will learn more about median and mode next year at the Statistics course!) misleading 7  17.12.2024 Outliers skewing the mean: Extreme Misuse of values can significantly affect the mean, averages to making it less representative of the mislead entire dataset. How averages can be Other misleading tactics involves selectively using either median or mean, manipulated to or using mean in bimodal distributions. distort reailty You will learn more about those statistical terms next year. Example: If 10 people in a room have a total net worth of $1 million, the mean is $1 million divided by 10, which equals $100,000. The mean can sometimes be misleading, especially with outliers. Outliers are values that are significantly higher or lower than the rest of the data. If one person in a group of nine has negative wealth while the rest have about $100,000 each, the mean is $33,222. This does not accurately represent the wealth of most people in the group. 8  17.12.2024 Example: Imagine you and two friends have started a small company with five employees. As the year comes to a close, you need to present the financial report to your team, hoping to make them convinced to hire new employees. Reporting profits per employee may make the company look more efficient to justify hiring. Average salary of employees: $66,000 Average salary of owners: $100,000 Annual profits per employee: $42,000 Graphical manipulations 9  17.12.2024 Truncating axes: Truncating the y-axis can Graphical exaggerate differences in data, making manipulations: trends appear more dramatic. Scaling and Scaling manipulations: Inconsistent scales Truncating on graphs can distort perceptions of relationships between data points. How visual data representations Double Y-axis: Using two different y-axes can mislead can make unrelated variables appear correlated, misleading viewers. What can you say about this graph? Unlabeled axis: What are HCs? We aren’t told, but from the context—they’re being compared with SZ 10  17.12.2024 Unlabeled axis: The y-axis is completely missing, so we don’t know what is being measured (is it units sold or dollars?), and we don’t know what each horizontal line represents. Truncating axes: The graph visually suggests that taxes will rise significantly, with the right-hand bar being six times taller than the left-hand bar. This gives the impression of taxes increasing sixfold—something nobody would want. 11  17.12.2024 Imagine a city where crime has been growing at a rate of 5 percent per year for the last ten years. Discontinuity in Vertical or Horizontal Axis: Using all the same data, just create a discontinuity in your x-axis. This will distort the truth and deceive the eye Double Y-axis: Using two different y-axes can make unrelated variables appear correlated, misleading viewers. 12  17.12.2024 Misleading correlations: Using different scale on two y-axes can falsely imply a Double Y-axis correlation between unrelated variables. deception Visual overload: Viewers often assume How multiple Y- relationships when two data sets are shown together, even if unrelated. axes mislead viewers Manipulating perception: Adjusting scales on the y-axes can make changes seem more dramatic or aligned. Which one is true? Misleading correlations: We should look the correlations! The first graph appears to be illustrating a correlation of 0, the second graph appears to be representing one that is close to 1. The actual correlation for this dataset is.91, a very strong correlation. Spending more on students is, at least in this dataset, associated with better SAT scores. 13  17.12.2024 Visual overload: Viewers often assume relationships when two data sets are shown together, even if unrelated. Plotting Things That Are Unrelated 14  17.12.2024 The scissors are cutting the bill not at 4.2 percent of its size, but at about 42 percent. Inconsistent units: Using different units for similar data points can confuse and Inconsistent mislead viewers. data representation Changing time intervals: Altering the Distorting intervals on the x-axis can change the perceived trend of data. truths through variable manipulation Selective data exclusion: Leaving out data that doesn’t fit the narrative can make results appear more favorable. 15  17.12.2024 News reports indicated that 2014 was one of the deadliest years for plane crashes, with 22 accidents leading to 992 fatalities. However, air travel is actually safer today than ever before. Due to the vast increase in the number of flights, these 992 fatalities reflect a significant decrease in the number of deaths per million passengers (or per million miles flown). On any given flight with a major airline, the odds of dying are approximately 1 in 5 million, making it far more likely that you could be killed doing almost anything else—like crossing the street or even eating (with death from choking or accidental poisoning being roughly 1,000 times more likely). U.S. News & World Report compared the proportions of Democrats and Republicans from the 1930s onwards, but the sampling methods have changed significantly over time, making the comparisons unreliable. Early sampling favored wealthier individuals with landlines (who leaned Republican), while later methods included cell phones, which attracted younger, more Democratic-leaning respondents. Because of these evolving sampling techniques, it’s unclear if the actual proportion of Democrats to Republicans has changed, as the data over time are not truly comparable. 16  17.12.2024 Data Sampling techniques: The method of selecting participants can affect the collection reliability of data. Random sampling is ideal methods for minimizing bias. Surveys and questionnaires: The way The questions are phrased can influence responses, leading to biased data. foundation of reliable Observation and experimentation: Controlled experiments provide reliable data informatio but may lack real-world applicability. n Every time we read a result in the newspaper that 71 percent of the British are in favor of something, we should reflexively ask, “Yes, but 71 percent of which British?” 17  17.12.2024 Evaluating words How do we know? Evaluating credibility of information sources Authority of the source: Evaluate whether the source has recognized expertise or credentials in the subject area. Bias and objectivity: Assess if the source has a potential conflict of interest or inherent bias that could influence the information. Cross-referencing: Verify the information by checking multiple reputable sources to ensure accuracy. 18  17.12.2024 Credentials and experience: Check if the Identifying author has relevant education or extensive experience in the subject matter. expertise How to Peer recognition: Experts are often cited by other authorities or participate in peer- determine reviewed publications. if a source Affiliations and publications: Review the is truly an institutions or organizations the author is associated with to determine their expert reliability. Confirmation bias: We tend to favor Overlooked information that supports our existing beliefs, leading us to ignore alternative alternative explanations. explanations Complexity of causes: Most events have The multiple potential causes, and considering importance of only one can lead to oversimplification. considering Encouraging a broader view: Questioning multiple the first explanation that comes to mind possibilities helps uncover less obvious, but possibly true, alternatives. 19  17.12.2024 Hypothesis formation: The scientific method starts with a question or hypothesis that can be tested. How science Works Experimentation and observation: Conducting controlled experiments to gather The scientific data, which can either support or refute the method as a hypothesis. tool for truth Peer review and replicability: Findings must be reviewed by peers and reproduced to be accepted as valid knowledge. Knowing what you don’t know The importance of acknowledging knowledge gaps Overestimating our knowledge can lead to poor decision making, true experts recognize the limits of their understanding. Humility in learning: Acknowledging gaps in knowledge is the first step toward gaining deeper understanding and expertise. Continuous inquiry: Curiosity and asking questions are crucial to expanding our understanding and avoiding false confidence. 20  17.12.2024 Conclusion: Developing your critical thinking Understand different types of data: Learn to evaluate numbers, words, and visual information critically to identify potential manipulations. Question sources and context: Always consider the credibility of information sources and the context in which data is presented. Practice lifelong inquiry: Adopt a mindset of continuous questioning and learning to refine your understanding and resist biases. 21