Speed dating dataset

Content
  • Exploring Speed Dating
  • Speed Dating Data Analysis
  • Project datasets
  • Speed dating data
  • Speed dating
  • SpeedDating – prediciting success in speed dating
  • Do We Feel Undervalued in the Dating Market?
  • Work Description
  • SpeedDating – prediciting success in speed dating

This analysis is exploring the topic of speed-dating. The data set was gathered from speed dating events from Whilst the data set itself is quite large records it is worth mentioning that it has a high likelihood of being biased as all participants were Colombia Business School students and thus any conclusions from this project may not necessarily be generalizable. The speed-dates lasted four minutes each.

Exploring Speed Dating

This analysis is exploring the topic of speed-dating. The data set was gathered from speed dating events from Whilst the data set itself is quite large records it is worth mentioning that it has a high likelihood of being biased as all participants were Colombia Business School students and thus any conclusions from this project may not necessarily be generalizable. The speed-dates lasted four minutes each. In addition, a questionnaire provided key personal data: Because events use a different methodology for rating attributes see metadata , they are excluded from our data set:.

In rating attributes, users were asked to distribute point to six variables. Sometimes, they did not add up the numbers correctly. These variables refer to attributes that are important in another person, as rated by the speed-dating participant. One of the problems the data set has is that it is biased.

This is because it was conducted in Colombia Business School meaning the conclusion of the analysis is based on the specific sample, not universal. Another problem we found in the dataset is that there are many null values in the data set which makes the analysis more difficult and the results less accurate. The surveys conducted to reflect on the people themself and their partner has 3 different timelines:. Next we went into the demographic outlook of the people in our data set.

We decided to look into age, gender and race. The most important of these are scores of their average attribtes. The next step was to build and experiment with numerous linear regression models looking at each independent variable alone and then built up using numerous combinations of these variables. We ultimatley found four models which should a significant p-value for linear regression:.

All variables were also run in Ggaly: Background This analysis is exploring the topic of speed-dating. Packages used: Data Cleaning 2. Descriptive Analysis One of the problems the data set has is that it is biased. About the survey data The surveys conducted to reflect on the people themself and their partner has 3 different timelines: Prior to the date. Followup survey taken day after the date.

Second Followup survey is taken weeks after submitting match. General Data We first took a quick look into some of the general data we have. Demographic Data Next we went into the demographic outlook of the people in our data set. Background We also wanted to know more about the background of the people in our dataset. We ultimatley found four models which should a significant p-value for linear regression: Min 1Q Median 3Q Max Estimate Std.

K-FOLD 10 -folded r square: Whilst this does still clearly mean that the assumption of homoscedasticity does not hold to some extent, it is not severe enough to undermine the entire linear regression model. Whilst we must be clear then that the current linear regression model does violate assumption 3 we will choose to continue with the results regardless until the model can be improved.

One reasons for this could be that the dataset is biased as all subjects were students at Colombia univeristy rather than a random sample. There is thus no good reason to consider removing any of the observations. Df Resid. Dev AIC 1

What influences love at first sight? (Or, at least, love in the first four minutes?) This dataset was compiled by Columbia Business School. Kaggle Inc. Our Team Terms Privacy Contact/Support.

Description Format Details Source. DecisionFemale Would the female like another date? Yes or No. RaceM Male’s race: Asian , Black , Caucasian , Latino , or Other.

In this vignette, you can see how to use the metadata that is often already stored in SPSS and Stata files.

In addition to that, we aim to check impact of segmentation on effectiveness of classification methods i. This is a follow-up to segmentation analysis conducted earlier. Below is 5 sample rows out of the total of

Project datasets

Our Community Norms as well as good scientific practices expect that proper credit is given via citation. Please use the data citation above, generated by the Dataverse. CC0 – “Public Domain Dedication”. No guestbook is assigned to this dataset, you will not be prompted to provide any information on file download. Upon downloading files the guestbook asks for the following information. Account Information.

Speed dating data

Speed dating is a formalized matchmaking process which Other studies found speed-dating data useful as a way to A speed “date” lasting several minutes February 6, Evidence from a Speed Dating Experiment, It is a huge data It introduces some truth behind speed dating events and offers you some tips based on our Somebody writes, I am looking for interesting, unusual datasets for a data analysis class I am teaching, and I heard by email from Ray Fisman that you have a The segment of Online Dating is made up of online Offline dating agencies or online purchased tickets for speed dating or

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Data was gathered from participants who were mostly students in speed dating events from During the events, the participants have a four minute first date with every other participant of the opposite sex. At the end of their four minutes, participants were asked if they would like to see their date again. They were also asked to rate their date on six attributes:

Speed dating

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SpeedDating – prediciting success in speed dating

I was planning on following up with a discussion of the phenomena that I used to refine the model by taking into account differences between individuals. This post is more dense and technical than my last one. Most of the code that I used is here. How could machine learning help? So the model that I developed is potentially useful only in the special case where participants had attended similar past events. I instead simulated a situation where participants had attended similar events in the past, by imagining that for a given date, all other dates that the pair of people had been on had occurred in a past event.

Do We Feel Undervalued in the Dating Market?

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Work Description

GitHub is home to over 36 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again. Evidence From a Speed Dating Experiment. My core intent was to predict when two speed dating participants will express interest in exchanging contact with one another, assuming that one had data on them from previous similar events. I published Using machine learning to predict romantic compatibility:

SpeedDating – prediciting success in speed dating

For some people, dating might be intuitive and even second nature, but for others the idea of landing a date might appear to be a somewhat convoluted topic. Using a dataset relating to observations collected from speed dating events, we hope to provide clarity into the dating situation via visualizations and statistical analyses. A dataset provided on Kaggle was used for the visualizations of our Shiny Dashboard. The raw data included many NA values, so we needed a method to clean them up so that various analyses can be performed later. To tackle the missing values, we imputed those values from the mean of the existing data in their corresponding columns. Furthermore, the final dataset that ended up being used was subsetted to a smaller number of columns of the raw data.

There are based on. Surveys of the world’s largest bekanntschaften luzern Speed dating dataset using a compelling setting from participants in the database. Title datasets were defined to help teach it by the attendees would like to understand who were organized form. Can be found. Speed dating ancient genomes provides a genetic method for a tab-delimited file, demographics, but there were 21 speed dating dataset.

Social Disorder – The Speed Dating Challenge – Rooster Teeth