Describing scatterplots (form, direction, strength, outliers) (article) | Khan Academy (2024)

Want to join the conversation?

Log in

  • Art Lightstone

    6 years agoPosted 6 years ago. Direct link to Art Lightstone's post “In Problem #3, illustrati...”

    In Problem #3, illustrations A and B, you show something we see in economics quite a bit. In economics, we're always interested in identifying "effects" that take place between variables. However, sometimes one effect drops off and then a new effect takes over. I call this phenomenon a "split" effect.

    For example, in the Laffer curve, we at first see the government raise more tax revenue as tax rates increase because they collect more money from citizens. Simple enough. However, after a certain tax rate is reached, we start to see a new effect take place wherein the tax revenue drops off as the tax rate is increased further. This is because at very high rates of taxation, people either lose interest in working, or they start to seek ways of hiding their income from the government. Thus, we often see two or more different effects express themselves through a full range of data.

    While I have always used the term "split" effect to describe such phenomenon, I have not been able to find this phenomenon acknowledged or identified (by any particular term) amongst economists or mathematicians. Mathematicians seem to simply call these scenarios "non-linear" or "curvilinear" relationships, without seeming to notice that there are invariably two distinct relationships being identified by the data.

    Am I mistaken? Do mathematicians acknowledge split effects? If so, what term do mathematicians use to describe this type of phenomenon?

    (41 votes)

    • goldeneggs100

      6 years agoPosted 6 years ago. Direct link to goldeneggs100's post “Mathematicians probably i...”

      Mathematicians probably include your "split effect" in the category of nonlinear correlation

      (5 votes)

  • Andrew McClellen

    6 years agoPosted 6 years ago. Direct link to Andrew McClellen's post “aren't there too many out...”

    aren't there too many outliers in problem 2 !*

    (6 votes)

  • Arbaaz Ibrahim

    5 years agoPosted 5 years ago. Direct link to Arbaaz Ibrahim's post “How is it possible to tel...”

    How is it possible to tell whether the correlation is strong or moderately strong?

    (5 votes)

    • Mahak Azeem

      4 years agoPosted 4 years ago. Direct link to Mahak Azeem's post “Strong correlation means ...”

      Strong correlation means that there aren't many outliers. In simple words, the dots on the graph are close to each other.

      (3 votes)

  • 27boubekeryounes

    a year agoPosted a year ago. Direct link to 27boubekeryounes's post “How many points have to b...”

    How many points have to be off course for a graph to be a "moderately negative or positive"

    (4 votes)

    • Said Almasri

      a year agoPosted a year ago. Direct link to Said Almasri's post “Is not about the amount, ...”

      Is not about the amount, but the direction, if they have a downwards tendency then they are negative, and a topwards is a positive.

      (3 votes)

  • Jenny B

    4 months agoPosted 4 months ago. Direct link to Jenny B's post “we are so up!”

    we are so up!

    (3 votes)

    • KassL

      4 months agoPosted 4 months ago. Direct link to KassL's post “ong brotheren”

      ong brotheren

      (1 vote)

  • jacob collier

    4 years agoPosted 4 years ago. Direct link to jacob collier's post “no questions i understand”

    no questions i understand

    (3 votes)

  • FREEDA252

    4 years agoPosted 4 years ago. Direct link to FREEDA252's post “i just realy needed work ...”

    i just realy needed work for the carona brake

    (3 votes)

  • sa06383

    4 years agoPosted 4 years ago. Direct link to sa06383's post “why hast this world lose ...”

    why hast this world lose its mind?

    (3 votes)

  • Joyce Layton

    2 years agoPosted 2 years ago. Direct link to Joyce Layton's post “connections between propo...”

    connections between proportional relationships, lines, and linear equations]

    (2 votes)

    • Jerry Nilsson

      2 years agoPosted 2 years ago. Direct link to Jerry Nilsson's post “A proportional relationsh...”

      A proportional relationship is of the form 𝑦 = 𝑘𝑥,
      which is also the equation of a straight line that goes through the origin.

      An example of a proportional relationship would be the outcome of rolling a six-sided die 𝑥 times.
      Given that the die is fair the average outcome per roll is 𝑘 = 3.5
      Thus the expected outcome after 𝑥 rolls is 𝑦 = 3.5𝑥

      If we ran a bunch of simulations where 𝑥 varies from, say, 1 to 20
      and we plotted the results we would most likely get something that resembles the line 𝑦 = 3.5𝑥

      (3 votes)

  • rosymacs23

    2 years agoPosted 2 years ago. Direct link to rosymacs23's post “why is it strong negative”

    why is it strong negative

    (2 votes)

    • Airr_

      a year agoPosted a year ago. Direct link to Airr_'s post “Negative does not necessa...”

      Negative does not necessarily mean that the points are spread out. Negative just means that the trend line/points are going downwards. Positive is upwards. Positive/negative is the direction of the line, not the strength.
      Hope this helps ;)

      (2 votes)

Describing scatterplots (form, direction, strength, outliers) (article) | Khan Academy (2024)

References

Top Articles
Latest Posts
Article information

Author: Aracelis Kilback

Last Updated:

Views: 6524

Rating: 4.3 / 5 (64 voted)

Reviews: 95% of readers found this page helpful

Author information

Name: Aracelis Kilback

Birthday: 1994-11-22

Address: Apt. 895 30151 Green Plain, Lake Mariela, RI 98141

Phone: +5992291857476

Job: Legal Officer

Hobby: LARPing, role-playing games, Slacklining, Reading, Inline skating, Brazilian jiu-jitsu, Dance

Introduction: My name is Aracelis Kilback, I am a nice, gentle, agreeable, joyous, attractive, combative, gifted person who loves writing and wants to share my knowledge and understanding with you.