1st year exam prep Flashcards
Quantitative data: Meaning, Types and Examples
Number or quantity of data.
Discrete: Counts of things (occurrences, amounts of qualitative data)
Continuous: Numerical scale measured over time (number of degrees, seconds, meters)
Qualitative data, Meaning, Types and Examples
Standard is just Data giving information on something. Verbal or narrative data. It can also be;
Nominal: Numerical coding (reference number)
Ordinal: Giving a ranking or order to something (Best to worst)
Define: Mean, Mode, Median, Range, Standard Deviation
Average, Most common, Middle, Max-Min, spread of data
Explain Histograms
Graph of “bins”(class boundaries) against frequency of data falling into that bin. Bar chart can be expressed as line. Skewed = non symmetrical. Tail = lines from peak
“Long tail right” Indicates that mean is above median
Equation for standard deviation:
s = SQRT((sum(x-mean)^2)/(n-1))
A larger S means more unrealiable data / worse quality
Explain Quartiles
Median = middle value
25th percentile = middle of bottom and median
75th percentile = middle of top and median
IQR = 75th - 25th
Points may be in-between numbers if even numbers left and right
Method of least squares
Equations are given - solve them simultaneously
r^2 = 1 - ∑(y.-(fx.)) / ∑(y.-Ymean)
r^2 = 1- (SUM e / SUM(y-ymean)
The closer r^2 is to 1, the better the fit.
So if SUM e = 0 then its a perfect fit!
Matrices need to know:
Multiplying rules (add when multiplying)
(R1xC1)(R2xC2) C1 and R2 need to match. And will make a (R1xC2) matrix
Representing in matrix form be careful with negatives
Transposes flip the matrix
Polynomial roots
Highest power equals number of roots (real or imaginary)
Bisection method
Xr = Xlower + Xupper / 2
Use side which has a sign change and repeat with new uppers and lowers
Error value = Xr new - Xr old / Xr new
Newton-Raphson method
Xnew = X - F(x)/F’(x)
Error value = Xr new - Xr old / Xr new
Z-score
Z= (x - xaverage) / s
Determines how many sd’s the x value is from the mean
What is Categorical data?
Both nominal and ordinal data. So a numerical coding giving rank to something. (10=great 1=terrible etc.)
What is Interval Data?
Quantitative and Qualitative. So a count of Qualitative data. (how many cars are red, blue, black etc)
Counted in bin values (for the example it would be different colours)
displayed using histogram.
What are Garbage values?
Bits of data that don’t fit with others but can be explained