A straight line which best describes the data on a scatter plot is called a "line of best fit". The line could pass through some of the points, all of them, or none of them.
The answer will depend on the data values: there is no rule that fits all situations.
There is no single answer to this question. It depends on what you are trying to do. Both types of charts are designed to interpret data. Pie charts are best is you want to show how each data element fits into the entire data set. Bar charts are good for letting you see how each data element compares to other data elements in the data set.
A numerical fact
If it is done correctly it should. That is the purpose of a pie chart; to show how each data item fits into the entire data set.
Use a pie chart when you're comparing many things with percents to show how each part fits into the whole.
Yes. The exception arises when you have outliers.
The straight line that best fits the data on a coordinate plane is the Line Of Best Fit.
A best fit graph to some data is exactly that: it is a line which fits the data best according to some optimality criterion. There is a always a trade off in fitting a line to data: one can change the number of degrees of freedom of the underlying equation, which affects how close the line can get to the data points. With more degrees of freedom, the line can more closely approximate the data. This is not to say that more degrees of freedom are better: with too many degrees of freedom, one is merely fitting to the noise in the measurement of the data, and the line will predict subsequent data poorly, when both interpolating and extrapolating the existing data. This is an example of Occam's Razor: one must pick the simplest model which adequately fits the data.
The line of best fit is also known as the least square line. It uses a statistical technique to determine the line that fits best through a series of scattered data (plots). Using regression analysis, it finds the line that minimizes the amount of errors (deviations - the sum of vertical distance of data points from the line. The result is a unique line that minimizes the total squared deviations, statistically termed the sum of squared errors.
There are a lot of different types of graphs so it is inevitable that I will miss some but here are the main ones: Bar / column chart - use if your data is in groups - either categoric (fits into unordered categories such as colour) or split into groups (e.g. 0-10, 10-20, etc.). Histogram - extension to the bar chart - use if the data is split into groups that are unequal (e.g. 0-10, 10-15, 15-30, etc.). Scatter chart - use if all of the data is continuous (i.e. can be any value within a range (e.g. time/temperature). Line graph - extension to the scatter chart - has a line of best fit - use if the two sets of data on the x and y axis are related. Pie chart - use if you want to show fractions of the data (e.g. that over half of people have one car but that only a quarter have two) - the data must be categoric (described above).
It fits the known data.
The best Mac data recovery software will change over the years as technology changes. You will need to do some research to see what fits your needs and pocketbook. There are some that are apparently free. Other software can be purchased for around $100.
IT fits Utwonk
The objectives of selecting a data type for a field include ensuring data integrity by restricting the type of values that can be stored, optimizing storage space by choosing the most appropriate data type for the data being stored, and facilitating efficient data retrieval and manipulation by selecting a data type that best fits the operations that will be performed on the data.
Many times, more than one theory can support a given set of experimental data. Therefore, it is difficult to determine which of the many available theories best fits the data presented.
The answer will depend on the data values: there is no rule that fits all situations.
There is no single answer to this question. It depends on what you are trying to do. Both types of charts are designed to interpret data. Pie charts are best is you want to show how each data element fits into the entire data set. Bar charts are good for letting you see how each data element compares to other data elements in the data set.