Why Do Logarithmic Graphs Vary Despite Similar Equations?

In summary, the graphs of y=logx+log2x and y=log2x^2 are different because the first equation is undefined for x<0 while the second equation is defined for all values of x. However, when looking at the domain of each equation, they are essentially the same. This is because when x>0, the two graphs are identical. The reason for this is that the simplified form of y=logx+log2x is y=log2x^2, which has the same domain as the first equation. This is because log a+log b=log ab only when a and b are both positive.
  • #1
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I graphed y=logx+log2x and y=log2x^2 and the graphs came out a lot different. However when you simplify y=logx+log2x you actually get y=log2x^2! Any ideas about why the graphs are so different yet the equations are pretty much the same? thanx
 
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  • #2
Well notice that log(a) outputs real numbers only if a>0.

With that in mind, when x<0, in your first equation the inputs to the logs are negative so that function is not defined if you are graphing real numbers. The second equation is defined for x<0 because x2 yields a positive value.

If you look at the two graphs they are identical when x>0. When x<0, the first graph is undefined while the second graph is just an even extension of when x>0.Just as a note, when you are dealing with the function y=log(x)+log(2x), the domain that yields a real result is x>0. If you simplify the expression to y=log(2x2) then you have to remember that your domain is still x>0. In that sense the two functions are identical.
 
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  • #3
In other words, log a+ log b= log ab if and only if log a and log b both exist- that is, as long as a and b are both positive. If a and b are both negative, log ab exists even though log a and log b do not.
 

1. Why are log graphs used in science?

Log graphs are commonly used in science because they provide a way to visualize data that covers a wide range of values. This is especially useful when dealing with data that spans several orders of magnitude, as a log graph compresses the data to make it easier to interpret and compare.

2. How do log graphs differ from linear graphs?

Log graphs differ from linear graphs in that the scale on the y-axis is logarithmic instead of linear. In a linear graph, the distance between each tick mark on the y-axis represents the same change in value. In a log graph, the distance between each tick mark represents a multiplication factor, such as 10 or 100.

3. What are the advantages of using log graphs?

Log graphs have several advantages, including the ability to show a wide range of data in a compact and easy-to-read format. They also make it easier to compare data points that differ by several orders of magnitude. Additionally, log graphs can help identify patterns or trends in the data that may not be as apparent in a linear graph.

4. When should I use a log graph?

A log graph is best used when the data being plotted covers a wide range of values. This can include anything from measurements of small particles in physics to population sizes in biology. If the data has a large range of values and you want to see how they compare to each other, a log graph may be the best choice.

5. Are there any limitations to using log graphs?

While log graphs can be useful in many situations, there are some limitations to be aware of. One limitation is that they can be more difficult to read and interpret for those who are not familiar with them. Additionally, log graphs may not accurately represent the data if there are negative values or if the data does not follow a logarithmic pattern. It is important to consider the type of data being plotted when deciding whether or not to use a log graph.

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