Free statistics calculators designed for data scientists. This Scatter Plot Maker:

- Generated Scatter Plot
- Saves & Recycles Data

To use the calculator, enter the X values into the left box and the associated Y values into the right box, separated by commas or new line characters. Hit calculate. It will generate a scatterplot.

For easy entry, you can copy and paste your data into the entry box from Excel. You can save your data for use with this calculator and other calculators on this site. Just hit the "save data" button. It will save the data in your browser (not on our server, it remains private). Saved data sets will appear on the list of saved datasets below the data entry panel. To retrieve it, click the "load data" button next to it.

Can be comma separated or one line per data point; you can also cut and paste from Excel.

Saved in your browser; you can retrieve these and use them in other calculators on this site.

Need to pass an answer to a friend? It's easy to link and share the results of this calculator. Hit calculate - then simply cut and paste the url after hitting calculate - it will retain the values you enter so you can share them via email or social media.

Scatter plots are an important tool for data scientists to visually analyze the relationship between two variables. A scatter plot maker is a useful tool that allows users to easily create scatter plots for data analysis. The scatter plot maker mentioned in the source is a free statistics calculator designed for data scientists. This article will discuss the features of this scatter plot maker and why scatter plots are a useful analytic tool.

The scatter plot maker discussed in the source has several features that make it a useful tool for data scientists. The calculator allows users to enter X and Y values into the left and right boxes, respectively, and then generate a scatterplot. The tool also allows for easy entry of data from Excel by copy and pasting the data into the entry box. Additionally, the scatter plot maker has a "save data" button that allows users to save their data for use with this calculator and other calculators on the website. This feature is helpful for users who want to compare different data sets or revisit a previous analysis.

The scatter plot maker generates a scatterplot in which the X-axis represents one variable and the Y-axis represents the other variable. Each point on the scatterplot represents a pair of values for the two variables. The scatterplot can be used to determine if there is a relationship between the two variables and, if so, what type of relationship exists.

Scatter plots are a useful analytic tool because they can visually represent the relationship between two variables. This relationship can be either positive or negative. A positive relationship means that as one variable increases, the other variable also increases. A negative relationship means that as one variable increases, the other variable decreases.

Scatter plots can also be used to identify outliers. An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. Outliers can affect the relationship between the two variables and can skew the results of the analysis. By visually identifying outliers on a scatter plot, data scientists can determine if they should be removed from the analysis.

Scatter plots can also be used to identify patterns in the data. These patterns can be used to make predictions about future data. For example,if a scatter plot shows a positive relationship between the number of hours studied and the grade received on a test, a data scientist can predict that students who study more hours will receive higher grades on future tests.

Another use of scatter plots is to determine if there is a correlation between the two variables. Correlation is a statistical measure that indicates the degree to which two variables are related. A scatter plot can show the type of correlation that exists between the two variables. There are three types of correlation: positive correlation, negative correlation, and no correlation.

Positive correlation means that as one variable increases, the other variable also increases. Negative correlation means that as one variable increases, the other variable decreases. No correlation means that there is no relationship between the two variables.

Scatter plots can also be used to compare two sets of data. For example, a scatter plot can be used to compare the heights and weights of two groups of people. By visually comparing the scatter plots, data scientists can determine if there are any differences between the two groups.

In conclusion, a scatter plot maker is a useful tool for data scientists who want to quickly and easily create scatter plots for their data analysis. The scatter plot maker discussed in the source has several features that make it a useful tool, including the ability to enter data from Excel and the ability to save data for future use. Scatter plots are a useful analytic tool because they can visually represent the relationship between two variables, identify outliers, identify patterns in the data, determine correlation, and compare two sets of data. By using a scatter plot maker, data scientists can quickly and easily analyze their data and make informed decisions based on their findings.

For more information about analyzing scatter plots, check out this tutorial.- Critical Value Calculator (New!)
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- Critical value of Z
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- Bernoulli Distribution
- Chi Square Distribution
- F Distribution

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- Hypergeometric Distribution
- Beta Distribution
- Gamma Distribution
- Geometric Distribution
- Negative Binomial
- Lognormal Distribution
- Pareto Distribution
- Weibull Distribution