HELP with problems with lab. UPLOADED PICS

[gnome222]

I am doing lab for physics and I have doe problems. I will appreciate any help thanks.
1) How do you calculate the error in raw data?
2) How do you use this equation Δmave = (mmax – mmin)/2
I have example but I have no idea where do you get the max and min. This equation is for calculating the error( + or - ) for the average.

 

[mfb]

Welcome to physicsforums!

1) How do you calculate the error in raw data?

That depends on your experiment and data. There are tons of books about that topic, there is no way to give a simple general answer.

I have example but I have no idea where do you get the max and min.

Neither do we because you shared exactly nothing about your experiment or the background of the equation.

 

[gnome222]

Welcome to physicsforums!
That depends on your experiment and data. There are tons of books about that topic, there is no way to give a simple general answer.
Neither do we because you shared exactly nothing about your experiment or the background of the equation.

This is the example that i got. how would you calculate Δmave = (mmax – mmin)/2 for this particular example. Like, i can't figure out where they got the max and min from.thanks

 

[gneill]

gnome222, Please use the homework template that is provided when you start a new thread in the homework area of Physics Forums.

The data for your M_ave and ΔM_ave comes from the raw data:

For each line of data the M_ave value is the arithmetic average of the raw data entries for the "mass of rice", rounded to two significant figures.

The ΔM_ave takes the largest and smallest values in one line of data and forms the average of them. In the first table you presented (which is reduced data, not raw data), each entry in the Average Hanging Mass column should have a corresponding ΔM_ave accompanying it.

 

[gnome222]

gnome222, Please use the homework template that is provided when you start a new thread in the homework area of Physics Forums.

The data for your M_ave and ΔM_ave comes from the raw data:
View attachment 74349

For each line of data the M_ave value is the arithmetic average of the raw data entries for the "mass of rice", rounded to two significant figures.

The ΔM_ave takes the largest and smallest values in one line of data and forms the average of them. In the first table you presented (which is reduced data, not raw data), each entry in the Average Hanging Mass column should have a corresponding ΔM_ave accompanying it.

Hmmm. So how would you calculate the error? Thanks for response.

 

[gneill]

Hmmm. So how would you calculate the error? Thanks for response.

The error in what? It looks like they are taking the raw data and claiming an error of ±ΔM_ave for the average values.

 

[gnome222]

The error in what? It looks like they are taking the raw data and claiming an error of ±ΔM_ave for the average values.

I mean the error in trials. The .1 g. Or it is just the precission of their instrument by which that are measuring.

 

[gneill]

I mean the error in trials. The .1 g. Or it is just the precission of their instrument by which that are measuring.

Well, I don't know what the equipment was or the lab setup, or in fact what the objectives were for the lab. I can only go by what you've presented so far. From what I can tell, for each "wooden block" a set of 5 trials of some sort were performed leading to five quantities of rice whose masses were then measured by some equipment with a stated accuracy of ±0.1g . But it seems that something in the nature of the setup leads to a much larger variation in those masses of rice. So I'm not sure what it "means" to measure those values to an accuracy of 0.1g when they vary by an order of magnitude or two more than that.

If you want to know how accurate your averages are you can use the usual propagation of error formulas for addition and division to fix the accuracy of the averages. You can then check to see if the rounding to two figures is justified.

EDIT: If you do a web search on "error propagation" you will turn up lots of resources. For example, here's a page for a lab tutorial that gives basic formulas for determining and propagating the uncertainty in measured values (trials):

http://www.clemson.edu/ces/phoenix/tutorials/errorp/