help in assignment

2_Criticalthinking.pptx

Home >Business & Finance homework help >Management homework help >help in assignment

Short quiz on syllabus (graded)

It is not necessary to make an appointment to meet the prof (T / F)

Circle all 3 of the main objectives in this course:

(a) evaluate claims critically; (b) theorize creatively; (c) think simply; (d) develop an open mind; (e) diversity; (f) participate actively

Session A is when the prof lectures to review basic concepts (T / F)

How many unexcused absences do you get in this course?

(a) none; (b) 1; (c) 2; (d) 3; (e) 4; (f) 5

To encourage participation, the prof will rely primarily on:

(a) cold-calling; (b) intrinsic motivation; (c) team leaders; (d) magic

The due date for the first draft of the individual paper is:

Mar 9; (b) Mar 19; (c) Mar 29; (d) depends on team; (e) Apr 26

Which of the following are you not allowed to have in the classroom?

(a) Water; (b) coffee; (c) food (i.e., solid); (d) laptop; (e) all of above

Z302 – Spring 2013 Time Management Fundamentals

Once again:

If you anticipate legitimate absences during the semester, and you have written documentation of them (e.g., specific sporting events where you’re on the roster), feel free to bring them to me very early in advance.

I will record the specific dates in my notebook accordingly.

Z302 – Spring 2013 Time Management Fundamentals

Critical thinking training

Source:

Rick Ligthelm

© 2017 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.

Critical thinking tools

Can be grouped into four:

Tool #1: Ambiguous causality

Tool #2: Trivial magnitude

Tool #3: Misinterpretation of evidence

Tool #4: Lack of practical utility

Tool #1: Ambiguous causality

Tool #1: You say that A causes B. But, could it be the case that A does not cause B (or that A has only a small effect on B), because evidence more strongly supports an alternative model of the relationship between A and B? There are mainly two types of such alternative models:

Reverse causality: B causes A instead of the other way around.

Buying expensive suits (A) will make you rich (B).

Playing basketball (A) makes you over 6”6 tall (200cm) (B).

Supreme confidence (A) makes you a competent employee (B).

Tool #1: Ambiguous causality

Reverse causality: B causes A instead of the other way around.

Confound (i.e., “third”) variable: C causes both A and B.

Eating fat makes you fat. A possible “C” is _________.

Egalitarian policies (e.g., same pay) improves unit performance (e.g., firm revenue). A possible “C” is _________.

Job satisfaction is positively correlated with job performance. A possible “C” is _________.

Tool #1: Ambiguous causality

Reverse causality: B causes A instead of the other way around.

Confound (i.e., “third”) variable: C causes both A and B.

Advanced examples of using Tool #1 (either model applies):

Our research team identified 11 companies that became good (i.e., average) to great (i.e., outperforming the market average by multiples over many years). From these 11 companies, we distilled 7 characteristics that make good companies great.

We asked each employee to rate both their manager’s charisma and one’s own performance. As a result, we found that employees with charismatic managers tend to outperform other employees.

Tool #2: Trivial magnitude

Tool #2: Even if A does cause B, what is the magnitude of this relationship? Is it large enough to be important?

Is it large enough? A correlation refers to the strength of the relationship between two variables.

Perfect positive relationship (i.e., upper limit): 1

Perfect negative relationship (i.e., lower limit): -1

Rule of thumb: r = .10 is weak, .30 is moderate, and .50 is strong in the organizational behavior context. But ultimately the question of whether .30 or even .50 is large enough depends on the context (e.g., cost to implement the newly proposed training program).

You have to square the r value to be able to say that a predictor explains x% of the variance in the dependent variable.

Tool #2: Trivial magnitude

This virtually never happens in OB research. Perhaps the correlation gets pretty close to 1 (e.g., .995) in certain literatures in physics that rely on high precision measurement and extremely controlled (i.e., sanitized) lab experiments.

Tool #2: Trivial magnitude

On average, in the social sciences (including education, OB, social psychology), the typical correlation is around .20 to .30.

Tool #2: Trivial magnitude

Which of the predictors would you say have trivial magnitudes based on their correlations you see below?

The screenshot of Schmidt & Hunter (1998, psych bulletin) table 1.

Tool #2: Trivial magnitude

Another example of trivial magnitude:

Deliberate practice: “practice that focuses on tasks beyond your current level of competence and comfort. You will need a well-informed coach not only to guide you through deliberate practice but also to help you learn how to coach yourself” (Ericsson et al., 2007, HBR).

Proponents, including Malcolm Gladwell (author of Outliers), argue that deliberate practice accounts for performance differences even among elite performers.

So, let’s look at the hard evidence to evaluate Gladwell’s claim.

Tool #2: Trivial magnitude

Overall, deliberate practice accounted for 18% of the variance in sports performance. However, the contribution differed depending on skill level.

Most important, deliberate practice accounted for only 1% of the variance in performance among elite-level performers.

This finding is inconsistent with [Gladwell’s] claim that deliberate practice accounts for performance differences even among elite performers.

Tool #3: Misinterpretation of evidence

Tool #3: You say that A causes B, and the magnitude of this relationship is non-trivial. In doing so, you cite these various studies as your evidence. However, I remain skeptical because you might have failed to interpret the evidence correctly. For instance:

You confused a positive correlation with a negative one (or vice versa).

Your citations consist of anecdotes (i.e., “anecdotal evidence”) rather than experiments or statistical analyses of data.

You failed to mention the caveat that your claim is based on one or few studies, as opposed to an entire body of findings (e.g., meta-analyses).

You only look at linear trends, while ignoring non-linear trends, heteroskedasticity, and other informative information from the data.

Larger variance among the lower annual salary countries means more risk/uncertainty as to how happy you’ll be. Smaller variance among the higher annual salary countries mean a better guarantee of happiness.

Tool #3: Misinterpretation of evidence

Tool #3: You say that A causes B, and the magnitude of this relationship is non-trivial. In doing so, you cite these various studies as your evidence. However, I still remain skeptical because you might have failed to interpret the evidence incorrectly.

Another exercise: Planes that survive and come back from battle tend to have most bullet holes near their ‘bellies,’ so we should reinforce those areas to increase their defenses against enemy fire. What do you think officer? (Answer on next bullet point)

The misinterpretation is based on an incorrect understanding of the correlation’s sign.

Answer: Bullet holes around the belly positively relates to survival, not negatively.

Tool #3: Misinterpretation of evidence

Yet another exercise: We collected data on 16,422 newcomer players in Major League Baseball and 3,649 players in the National Basketball Association—belonging to 135 batter cohorts (from year 1871 to 2005), 135 pitcher cohorts (1871-2005), and 60 basketball cohorts (1946-2005). Results indicated that allocating varying amounts of opportunities does not lead to the emergence of star performers. (Answer on next bullet points)

Range restriction refers to the artificial reduction of a predictor or outcome’s variance. It tends to deflate (i.e., attenuate) correlations, thus often explaining why a relationship is found to be weak or non-existent.

Often occurs when the sample is too narrow/specialized and/or small.

Tool #2: Trivial magnitude

Caveat: It could be that this null correlation was obtained from data collected in a unique context that suppresses X from causing Y (e.g., lifting weights lead to muscle growth, but if you limit data collection period to 2 days, you’ll get zero correlation).

Tool #3: Misinterpretation of evidence

Graphical illustration of range restriction

Tool #4: Lack of practical utility

Some findings are so obvious or vague that they don’t translate to practical actions. Or, in the least, their usefulness only applies to very limited circumstances.

For example, hindrance stressors (i.e., stressors that tend to be appraised as thwarting progress) negatively impacts job performance.  This statement is to a certain extent tautological and, therefore, uninformative.

Tool #4: Lack of practical utility

Tool #4: You say that A causes B, and the magnitude of this relationship is non-trivial. Also, you do not misinterpret the underlying evidence. That’s all great. But I’m still skeptical because the relationship between A and B seems to lack practical utility. For instance, some findings are so obvious or vague that they don’t translate to practical actions. Or, in the least, their usefulness only applies to very limited circumstances.

An exercise: Goal setting theory states that assigning employees (1) specific and (2) difficult goals will result in higher levels of performance than assigning no goals, easy goals, or do-your-best goals. E.g.,

Raise $50,000 for a charity by June 20, 2017.

Reduce employee theft by 50% in the next financial year.

Finish the landscaping project within 1 week.

In what ways might goal setting not be very useful for a manager?

Goal: A certain outcome or level of proficiency to obtain within a specified time period.

Tool #4: Lack of practical utility

In what ways might goal setting not be very useful for a manager?

What constitutes “specific” and “difficult” may not be clear in advance, but instead only in hindsight (i.e., depending on the outcome). This is especially so in high-complexity jobs (i.e., cannot be easily scripted). (Next slide for graphical illustration)

Drills for critical thinking in OB

If goals are used in highly repetitive task situations, and if employees are more or less similar in terms of knowledge, skills, and abilities, then it may be reasonable to predict goal difficulty for someone else in advance. Otherwise, experience and intuition developed through trials and errors may be needed to truly find the “right balance” for oneself.

Another quick exercise: Replace the x-axis with conscientiousness (a personality trait). Assume the same non-linear trend in the figure. Would you use the resulting information to hire employees among applicants? Would you apply the same criticism based on lack of practical utility (i.e., finding the “right balance” is obvious only in hindsight)?

My reasoning on the follow-up exercise: No, because I could measure existing employees’ levels of conscientiousness and then use that to predict their job performance. The conscientiousness score (or score range) that predicts the highest level of job performance would be the “right balance”. There is no need for involving subjective judgment (e.g., regarding how specific and difficult something is).

Tool #4: Lack of practical utility

Tool #4: You say that A causes B, and the magnitude of this relationship is non-trivial. Also, you do not misinterpret the underlying evidence. But I still remain skeptical because I’m concerned that the relationship between A and B may lack practical utility. There are mainly two forms of this criticism:

Some findings are so obvious or vague that they don’t translate to practical actions.

The finding is redundant with prior research (“old wine in new bottles”).

The definitions are highly similar or essentially identical when examined closely.

When measured, the concept correlates very highly with one or more other existing concepts (Cole et al., 2012; Harter & Schmidt, 2008).

Tool #4: Lack of practical utility

Examples of concepts that demonstrate signs of redundancy—both conceptually and empirically:

Various leadership styles redundant with each other

Engagement and motivation

Emotional intelligence redundant with cognitive intelligence

Organizational commitment redundant with job satisfaction

For example, Le, Schmidt, Lauver, and Harter (2007) showed that after the appropriate corrections for measurement error, the lower bound correlation between job satisfaction and organizational commitment was .92, and this value was the same whether the corrections were made via structural equations modeling methods or a newer method derived from generalizability theory. Moreover, Harrison, Newman, and Roth (2006) pointed out that the pattern of correlations found in individual studies and in meta-analyses makes it ‘‘reasonable to treat job satisfaction and attitudinal [organizational] commitment as specific reflections of a general attitude, as each is a fundamental evaluation of one’s work experiences’’ (emphasis in original). Also see Harter & Schmidt (2008) published in Industrial and Organizational Psychology.

For counterproductive work behaviors, see Hershcovis (2011, JOB).

Pop quiz on critical thinking tools (not graded)

“Playing the computer game Starcraft increases one’s IQ. That is, we found that people with higher IQs tend to play more Starcraft. Thus, we recommend that employees play more Starcraft to boost their IQ and therefore their job performance.” This is potentially a misleading statement because it ignores the possibility of ____ caused by ____. Fill in the two blanks by choosing two of the following options:

(a) Lack of practical utility; (b) misinterpretation of evidence; (c) self-selection; (d) trivial magnitude; (e) reverse causality; (f) redundancy

What is the general effect of range restriction on correlations?

(a) inflation; (b) deflation; (c) more practical; (d) less practical; (e) none of the above.

“I’d recommend that you smile less as a leader. One time, I had a leader who never smiled, and he was super effective.” This is a dubious claim because it relies on:

(a) Trivial magnitude; (b) one study only; (c) anecdote; (d) intuition; (e) goal-setting theory.

Z302 – Spring 2013 Time Management Fundamentals

Pop quiz on critical thinking tools (not graded) [continued]

Which of the following is NOT one of the main critical thinking tools that you should apply to a claim put in front of you?

(a) Trivial magnitude; (b) misinterpretation of evidence; (c) lack of practical utility; (d) ambiguous causality; (e) value compatibility.

“In our research, we found a .30 correlation between managerial feedback and employee job satisfaction.” This is traditionally seen as a _____ correlation, and it means that managerial feedback explains _____% of the variance in employee job satisfaction. Fill in the two blanks by choosing two of the following options:

(a) weak; (b) strong; (c) moderate; (d) trivial; (e) 30; (f) 9; (g) 3; (h) .30

Draw a figure to represent heteroskedasticity.

Z302 – Spring 2013 Time Management Fundamentals

Pop quiz on critical thinking tools (not graded) [continued]

Joe said, “The consultant talked a lot about the importance of creating new policies to reduce workplace incivility. But I read this meta-analysis showing that workplace incivility has a .91 correlation with with workplace aggression, against which we already have company policies.” Joe’s concern is essentially based on _______

(a) redundancy with prior research; (b) self-selection; (c) confound (i.e., “third”) variable; (d) vague findings; (e) obvious findings.

Which of the following correctly uses the confound variable argument to critique the claim that A causes B?

(a) C causes A; (b) C causes A and B; (c) C causes B; (d) C causes A, which in turn causes B; (e) all of the above.

True or false: The typical correlation in the social sciences is around .40 to .50.

True or false: A meta-analysis is a study of studies conducted to summarize the findings (e.g., correlations) in a research area.

Z302 – Spring 2013 Time Management Fundamentals

Why do people (i.e., consumers of research) buy into sloppy arguments?

Source:

Rick Ligthelm

Causes of uncritical thinking

Mental shortcuts (i.e., minimization of effort; cognitive biases).

People use and crave them (e.g., Mike Chang’s “six pack shortcuts”).

Similar to me error: Similarity leads to attraction, so we tend to favor those who are similar to us.

“I went to UD. The presenter also went to UD. I like what what he’s saying.”

Halo error: If an employee receives a high score on one characteristic, she also receives a high score on other characteristics, even though her true scores may not be even across all of those characteristics.

“The pharmaceutical sales rep is good-looking and, therefore, what she is saying must be true. I will sign the contract and prescribe these drugs to my patients.”

https://www.youtube.com/watch?v= YQZ2UeOTO3I (3:40-5:30)

Sources: Black Swan by Nassim Taleb (2007); Thinking, Fast and Slow by Daniel Kahneman (2011); Cascio & Aguinis (2011)

Causes of uncritical thinking

Mental shortcuts (i.e., minimization of effort; cognitive biases).

Confirmation bias: The tendency to search for, readily accept, and/or recall information that is consistent with your beliefs. Also, the tendency to discredit or ignore information that is not consistent with your beliefs. Illustration:

Cult leader says: “The Martian gods have told us that the world will end on Dec. 31, 2012! We must begin performing the ritual Martian dance so that we will shoot straight up into Mars heaven when Earth explodes.”

[The planet Earth continues to exist just fine into the year 2013.]

Cult members ask the cult leader: “Hey man, what happened? We thought the world was supposed to end yesterday.”

Cult leader states: “The gods were so pleased with our dancing that they decided to spare us! This is proof that the gods are kind and generous!”

Cult members: “Yay!”

Sources: Black Swan by Nassim Taleb (2007); Thinking, Fast and Slow by Daniel Kahneman (2011); Cascio & Aguinis (2011)

Causes of uncritical thinking

Mental shortcuts (i.e., minimization of effort; cognitive biases).

Fundamental attribution error: Takes place when a supervisor attributes poor performance to an employee’s dispositional tendencies (e.g., personality, abilities) instead of the situation (e.g., poor equipment).

Causes of worldwide obesity: People all over the world deciding to get lazy all at the same time vs. significant change in the global food supply post-WW2.

Self-serving bias: Attribute bad events to external factors, while attributing good ones to internal factors. For instance, if Eugene suffers heavily from self-serving bias, he would say things such as the following:

Eugene says: “I bombed that test because the professor is such a jerk and won’t help me.”

Eugene says in an alternate reality: “I aced that test because I’m like so smart.”

Sources: Black Swan by Nassim Taleb (2007); Thinking, Fast and Slow by Daniel Kahneman (2011); Cascio & Aguinis (2011)

Causes of uncritical thinking

Mental shortcuts (i.e., minimization of effort; cognitive biases).

Hindsight bias: The tendency to think that you totally saw an event happening—but only after the event has occurred and even if you had no basis for predicting the event before its occurrence. AKA: “I knew it all along.” “Creeping determinism.”

History is pretty much one giant set of hindsight biases.

An economist argues in 2008: “I’ve been telling the media and policy-makers that a financial crash was coming. All the economic indicators were there. More importantly, the system is set up in a way that crashes are inevitable. Yet, people did not listen to me. Invest in gold.”

A skeptic: “Hey, I’ve been listening to your predictions for quite some time, and you always say a crash is coming, though never precisely when. So, you’re basically like a doomsday prophet who has to be right just once. Anybody can do that and it requires no exceptional skill.”

Sources: Black Swan by Nassim Taleb (2007); Thinking, Fast and Slow by Daniel Kahneman (2011); Cascio & Aguinis (2011)

Causes of uncritical thinking

Mental shortcuts (i.e., minimization of effort; cognitive biases).

Representativeness heuristics: Guessing an event’s probability based on its similarity with a description of the event, while ignoring base rates (e.g., Is Tom W a computer science major)?

Availability heuristics: Guessing an event’s probability based on how easily one can recall examples of the event (e.g., suicides at Cornell U.).

Sources: Black Swan by Nassim Taleb (2007); Thinking, Fast and Slow by Daniel Kahneman (2011); Cascio & Aguinis (2011)

Causes of uncritical thinking

People love telling and listening to stories (i.e., anecdotes) because they are more entertaining than statistics and experiments. Stories can provide the illusion of order to what may be random, and people prefer order to chaos.

This is also known as the narrative fallacy.

Causes of uncritical thinking

People love telling and listening to stories because they are more entertaining than statistics, experiments, and lectures. Stories can provide the illusion of order to what is purely random, and people prefer order to chaos. For example:

Centralization versus decentralization among intelligence agencies

Pearl Harbor (Dec 7, ‘41): Seen as due to decentralization. Arguments and competitions between Army vs. Navy. Led to the creation of CIA.

Bay of Pigs Invasion (Apr ‘61): Seen as due to centralization (e.g., “groupthink”). Not enough arguments and competition. FBI and CIA made to compete with each other.

Twin tower attacks (Sep 11, 2001): Seen as due to decentralization. Led to the creation of the Terrorist Threat Integration Center (which combines the anti-terrorist activities of both the FBI and CIA).

“Why was the Pacific fleet at Pearl Harbor so unresponsive to signs of an impending Japanese attack? Because, in the week before December 7, 1941, they had checked out seven reports of Japanese submarines in the area–and all seven were false.”

Intelligence agency failures described by Malcolm Gladwell (http://gladwell.com/connecting-the-dots/). Search term is: centraliz

Causes of uncritical thinking

People love telling and listening to stories because they are more entertaining than statistics and experiments. Stories can provide the illusion of order to what may be random, and people prefer order to chaos. Another example:

What was the secret behind Victor Niederhoffer’s financial success?

The probability may not be different from a coin flipping experiment / scam.

Second illustration (http://gladwell.com/blowing-up/). Search term is: luck

Causes of uncritical thinking

To boost ratings, the media is incentivized to take serious research and translate it to entertaining tidbits (that are unfortunately misleading).

https://www.youtube.com/watch?v=0Rnq1NpHdmw (5:36-7:48 &14:05-14:57)

Causes of uncritical thinking

Distorted incentives affecting producers of research

$: Funding from an entity w/ a clear agenda

Coca Cola helps Chicago get fit: https://www.youtube.com/watch?v= 7zBcT5lvY7w

Tenure and promotion pressures, as well as desire for fame, etc.:

File drawer problem: The suspected tendency of researchers to cherry pick what to submit for research, as well as the tendency of reviewers and editors to cherry pick what research they will accept for publication.

Outright fraud, though presumably rare (e.g., making up data)

Causes of uncritical thinking

Other things that producers of research do

Various forms of sloppy, imprecise, and uncritical thinking by producers of research

https://www.youtube.com/watch?v=0Rnq1NpHdmw (9:55-11:57)

Rationalizations if they mess up (we’re only human!)

https://www.youtube.com/watch?v=YuTuWCSTnkE

In short, science and the communication of it is riddled with problems. The antidote is to use the critical thinking tools to voice your skepticism.

But, do so in a polite and diplomatic manner to avoid creating haters.

Pop quiz on the causes of uncritical thinking (not graded)

Which of the following is a cause of uncritical thinking?

(a) Mental shortcuts; (b) various biases/heuristics; (c) the preference for stories; (d) oversimplification by the media; (e) all of the above

“We identified 11 companies that became good (i.e., average) to great (i.e., outperforming the market average by multiples over many years). From these 11 companies, we distilled 7 characteristics that make good companies great.” This research team is most likely suffering from the following cause of uncritical thinking:

(a) Halo error; (b) confirmation bias; (c) hindsight bias; (d) self-serving bias; (e) funding from an entity with an agenda

Stories can provide the illusion of order to what is purely random, and people prefer order to chaos. This statement refers to:

(a) Narrative fallacy; (b) file drawer problem; (c) distorted incentives; (d) goal-setting theory; (e) decentralization

Z302 – Spring 2013 Time Management Fundamentals

Illustration of applying critical thinking

Source:

Rick Ligthelm

Illustration

How does all the material so far help me practically?

Narrow down your future actions from a variety of options!

Apply the critical thinking tools to eliminate dubious options.

"Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.” – Sherlock Holmes –

Conduct cost-benefit analyses to weigh remaining options.

Especially if you have many options left after step #1, and if you want to prioritize among the remaining options and perhaps further eliminate options.

Illustration

If you want to get in better shape, you’ll notice that there are so many options out there, such as:

Running

Caloric restriction

Weightlifting

Intermittent fasting

Elimination of processed carbs

Low fat diet

Low carb diet

Green coffee bean pills

Steroids (Don’t do it kids)

Illustration

Apply the critical thinking tools to eliminate dubious options.

Intermittent fasting removed because of ambiguous causality (e.g., caloric restriction may lead to both intermittent fasting and weight loss)

Green coffee bean pills removed because of trivial magnitude (e.g., “clinical studies revealed that the relationship is close to nill”).

Low fat diet removed because of misinterpretation of evidence (e.g., Ancel Keys’ seven countries studies)

Low carb diet removed because of lack of practical utility (e.g., “I’m on a budget, and carbs are cheap”).

For example, look for meta-analyses. Don’t rely on one or few studies.

Illustration

Conduct cost-benefit analyses to weigh remaining options.

There are two key criteria you can consider in your cost-benefit analyses.

First, consider the causes of uncritical thinking, and then either eliminate or reduce the importance of one or more remaining options.

E.g., “I really want steroids to be the solution. But I realize I’ve been engaging in confirmation bias by only recalling instances when people got in shape with the use of steroids—but not those who didn’t despite its use or those who actually gained more weight while on it.”

Illustration

Conduct cost-benefit analyses to weigh remaining options.

There are two key criteria you can consider in your cost-benefit analyses.

Second, options that involve removing potentially harmful things should be weighed more heavily than options that involve adding potentially beneficial things because new things often come with side effects (i.e., iatrogenesis)

E.g., “I have a funny left ankle. So, even if running offers tremendous benefits for getting in shape, it would not be worth it for me.”