Anchoring Effect: How Gullible Are We?

By Matias Badino

The table shows the median answer provided by the interviewees for the control questions and each one of the anchors

Data

Data Collection Efforts● 286 people were surveyed over the period of

16 days. ● 133 interviewees were males and 153 were

females ● Age range was 6 to 75 years old.● Data was collected at the Carnegie Library,

Carnegie Science Center, Pittsburgh Gifted Center, Pittsburgh Minadeo, and at the streets of Squirrel Hill.

Evaluation Criteria

Very large (up to 20 million) and low estimates (as low as 371) were given for all anchors. I have decided to use the median instead of the mean to summarize the data to avoid the effect of those outliers.

As a criteria to evaluate the bias, I calculate the ratio of the biased answer with the answer of the control question rounded to the nearest integer. This number is called bias factor. A bias factor of 10 means that the biased answer is 10 times larger than the one given without anchor.

References[1] D. Kahneman, “Thinking, Fast and Slow”, Publisher: Farrar, Straus and Giroux, 2013.[2] Sex differences in human psychology, Wikipedia at http://http://en.wikipedia.org/wiki/Sex_differences_in_human_psychology.[3] A. Kudryavtsev and G. Cohen, “Behavioral Biases in Economic and Financial Knowledge: Are They the Same for Men and Women?”, in Advances in Management & Applied Economics, vol.1, no.1, 2011.

Anchor/Gender All Males FemalesControl 5,250 6,500 3,5131,000 3,000 4,000 2,75010,000 11,300 9,000 12,300100,000 55,000 36,664 69,1011,000,000 200,250 128,500 375,000

Conclusions

In this experiment, the anchoring bias was huge. In general, interviewees were highly biased when the question was loaded with an anchor. The bias factor is small (between 1 and 4) when the anchor is close to the control, but it can be up to more than 40 when the anchor is 1 million. These results confirm my first hypothesis.

Females were far more influenced by the anchoring effect than males. With the exception of the anchor 1,000, females bias factor was 4 times larger than those of males. This rejects my second hypothesis. This result seems to be in accordance with other studies [3].

Photographs

Materials

Jars (3), rice (2 pounds), scale (1), computer (1), clipboards (3), paper, printer (1), scissors (1), booklet (1), glue, reading material [1], spreadsheet tool, Internet.

Future WorkMore detailed analysis will be performed using the recorded age of the interviewees and the recorded time taken to provide the answers.

Introduction

My project is about something called the anchoring effect. The anchoring effect is a psychological phenomenon that is used in everyday life, from guessing rice in a jar to buying and selling a house. It is very important to understand how anchoring affects people to improve the every day's decision making.

Anchoring effect is the bias in the decision of a person by the previous introduction of an anchor. The anchoring effect has been proven on several psychological experiments [1]. In this project, I provide further proof of the anchoring effect and evaluate whether it affects differently males and females.

ProcedurePeople are asked to estimate the number of grains in a jar (see Picture A). The question asked is:

Do you think there are more or less than X grains in this jar? How many grains do you think there are?

where X is the anchor. Anchors for 1K, 10K, 100K, and 1M are used. A control question is also asked without providing any anchor (without the first question).

People of different ages and gender are surveyed at different days, times of the day, and places.

ProblemDetermine if there is a anchoring effect when people is asked to estimate the number of grains in a jar full of rice (see Section Procedure). Further determine if there is a difference of the bias between males and females.

HypothesesHypothesis 1: there is a positive correlation between the anchor and the answer provided.

Hypothesis 2: Males and females are equally affected by the anchor provided.

Rationale H1: estimating the number of grains in a jar is very difficult. Therefore, I expect the interviewee to be strongly influenced by the anchor provided.

Rationale H2: there is no conclusive evidence that demonstrate superiority in numerical estimation between genders [2], therefore, I expect the same anchoring effect in males and females.

1,000 10,000 100,000 1,000,0000

20

40

60

80

100

120

All

Males

Females

Anchor [number of grains]

Bia

s F

act

or

ResultsThe table and graph show the bias factor for each of the anchors, for males, females, and both together. There is a positive strong correlation of the bias factor with the anchor. This means that the larger the anchor, the larger the bias.

Observe that the anchoring effect is very large in this experiment. Females provided an answer that was up to 107 times larger than the answer they provide when no anchor is given.

(B) Clipboard with collected data (C) Carnegie Science Center(A) Jar with rice

Anchor/Gender All Males Females1,000 1 1 1

10,000 2 1 4100,000 10 6 20

1,000,000 38 20 107