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Descriptive statistics
methods of organizing, summarizing, and presenting data in informative way. Not estimating future populatio etc but only to summarize pst (i.e. canadian population over years)

Inferential statistics
methods used to estimate a property of a population using asample
Best guess of a population value based on a sample informationimpossible to test all of the population, so representative sample chosen

Qualitative data
identifies categories or attributes. Eg. colour, gender etc.

Quantitative data
has numerical attributes. It indicates how much or how many.

Discrete variables
can only assume certain values, and there are gaps between variables.(number of bedrooms)

Continuous variables
assume any variable within a specific range. (tire pressure)

At nominal level of measurement
observations of a qualitative variable can only beclassified and counted. There is no particular order to the labels. (colour of M&M’s, gender)

The properties of ordinal level
data are that data classifications are represented by sets oflabels that have relative values and can be ranked or ordered. Distance between valuesnon necessarily equal.

In Interval level data,
responses classify, indicate order, and the distances betweenconsecutive numbers are meaningful.Data are always numericalZero is a point on a scale – not necessarily the absence of a phenomenon or bottomof the scale

Ratio data
Interval data + absolute zero and the ratio of two number is meaningfulIn this case an absolute zero means the zero value represents the absence of thecharacteristic being studied.

Inferential statistics
methods used to estimate a property of a population using a sample.

Frequency table
a grouping of qualitative data into mutually exclusive classes showing thenumber of observations in each class.

Relative (class) frequencies
indicate the fraction of observations in each category (class)

A relative frequency distribution
is the decimal expression of the relative frequency, forall observations

Frequency distribution
a grouping of data into mutually exclusive classes showing the numberof observations in each class.1. Decide on the number of classes. 2 to the k rule. 2^k>n (k classes, n observations), e.g.2^k>40, k>ln(40)/ln(2), k>5.322, set k=62. Determine the class interval or width. �≥�−�/� where i=interval, H=max, L=min3. Set the individual class limits. Avoid overlapping or unclear class limits 1<=Rate<34. Tally the list prices into the classes.5. Count the number of items in each class. The number of observations in each class iscalled the class frequency.

Histogram
Like a bar chart, but used for quantitative dataHorizontal axis is continuous if data continuousBars are adjacentClass frequencies on vertical axis, class limits OR class midpoints on horizontal axis.

A frequency polygon
also shows the shape of a distribution and is similar to a histogram. Itconsists of line segments connecting the points formed by the intersections of the classmidpoints and the class frequencies.

