Biostats Lesson 2 Flashcards
Observation on 1 variable may be shown visually by putting the variable’s on 1 axis and putting the frequency on the other
Visual Presentation of Data
___ are best used to interpret the frequency distribution visually
Figures
___ wherein the no of units observed is on the y-axis while th measurements levels are on the x-axis
Bar graph
Frequency how much it occurs
Bar are usually proportional to each other
Histogram
Figure that shorthanded presents a histogram
Dot is placed at the center of the top of the bars and connected to form a polygon which better enunciates the data shape
Much more prevalent sa gitna rather than sa baba
Frequency Polygon
Basic graphs that can illustrate 1/more data sets in 1 graph
Can have 2 instance whereas sa freq poly and histogram nde pede
Starts where the data starts
Line graph
Have bath x and y axes on the arithmetic scale
Arithmetic Line graphs
Has the y-axis as a logarithmic axes
Nakacurve
Semilogarithmic Line Graph
Defined as the value usd to represent the center/middle of a st of data values
Can know average
Locates observation on a measurements
Central Tendency
Average value sum of all the observed values divided by the total no of observation
Most mathematical properties and most representatives dataset if not for outliers
Mean
Middle observation data when data has been arranged from lowest to highest (ascending order)
Rarely used to make inferential conclusions frmo but is used frequentily in healthcare and economics
Median
Most commonly observed value
has some clinical interest but seldomly used in stats
If 2/more values appear w/ the same frequency, each is a mode
Mode
Disadvatage of mode
a set of data may have no mode/may have more than 1 mode
Describes the spread of values in a given data set
Suggests how widely spread out observation are
Dispersion
Statistical measurement of the spread between no. in a data set, it measures how far each number in the set is from the mean(average) and this from every other no in the set.
Variance
Average amount of variability in dataset
Square root of variance
Tells you on ave how far each values lie from the mean
Standard Deviation
Values are generally far from the mean
high sd
Values are clustered close to the mean
Low SD
Sample population (kumbaga room 4 error)
Degree of Freedom
Average deviation of a data point from the mean, median, mode
Mean Deviation/ mean absolute deviation
Difference between the observed value of a data point and the expected value
Deviation
Provides the range where true value lies
Confidence Interval
Values that split sorted data/probability distribution into equal parts
Q-quantile divides sorted data into q-parts
Quantiles
Statistical term that describes a division of observation into 4 defined intervals based on the values of the data and how they compare to the entire set of observattion
Quartiles
Difference between the highest and lowest values
Range
In descriptive stats: set of data is size of the narrowest interval which contains all the data
Range
Difference between the 3rd and 1st quartile
Mminus lang ung 3rd sa 1st quartile
Interquartile Range
Type of quantiles obtained adopting a subdivision into 100 groups
Percentile
Number denoting the position of a data point within a numberic dataset by indicating the % of the dataset w/ a lesser value
Percentile
Caculated by divising an ordered set of data into 100 equal parts
Percentile
A measure of the asymmetry of a distribution
Horizontal imbalance
Skewness
A distribution is asymmetrical:
When its left and right side are not mirror images
Right skewness
Positive distribution
Left skewness
negative distribution
Zero skewness
0
Descriptive statistic used to help measure how data disperse between a distribution’s center and tails w/ larger values indicating a data distribution may have “heavy tails” that are thickly concentrated w/ observations/are king w/ extreme observation
Kurtosis
