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JDL > Biostats Lesson 2 > Flashcards

Biostats Lesson 2 Flashcards

1
Q

Observation on 1 variable may be shown visually by putting the variable’s on 1 axis and putting the frequency on the other

A

Visual Presentation of Data

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2
Q

___ are best used to interpret the frequency distribution visually

A

Figures

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3
Q

___ wherein the no of units observed is on the y-axis while th measurements levels are on the x-axis

A

Bar graph

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4
Q

Frequency how much it occurs

Bar are usually proportional to each other

A

Histogram

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5
Q

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

A

Frequency Polygon

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6
Q

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

A

Line graph

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7
Q

Have bath x and y axes on the arithmetic scale

A

Arithmetic Line graphs

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8
Q

Has the y-axis as a logarithmic axes

Nakacurve

A

Semilogarithmic Line Graph

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9
Q

Defined as the value usd to represent the center/middle of a st of data values

Can know average

Locates observation on a measurements

A

Central Tendency

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10
Q

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

A

Mean

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11
Q

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

A

Median

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12
Q

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

A

Mode

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13
Q

Disadvatage of mode

A

a set of data may have no mode/may have more than 1 mode

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14
Q

Describes the spread of values in a given data set

Suggests how widely spread out observation are

A

Dispersion

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15
Q

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.

A

Variance

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16
Q

Average amount of variability in dataset
Square root of variance
Tells you on ave how far each values lie from the mean

A

Standard Deviation

17
Q

Values are generally far from the mean

A

high sd

18
Q

Values are clustered close to the mean

A

Low SD

19
Q

Sample population (kumbaga room 4 error)

A

Degree of Freedom

20
Q

Average deviation of a data point from the mean, median, mode

A

Mean Deviation/ mean absolute deviation

21
Q

Difference between the observed value of a data point and the expected value

A

Deviation

22
Q

Provides the range where true value lies

A

Confidence Interval

23
Q

Values that split sorted data/probability distribution into equal parts
Q-quantile divides sorted data into q-parts

A

Quantiles

24
Q

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

A

Quartiles

25
Q

Difference between the highest and lowest values

A

Range

26
Q

In descriptive stats: set of data is size of the narrowest interval which contains all the data

A

Range

27
Q

Difference between the 3rd and 1st quartile
Mminus lang ung 3rd sa 1st quartile

A

Interquartile Range

28
Q

Type of quantiles obtained adopting a subdivision into 100 groups

A

Percentile

29
Q

Number denoting the position of a data point within a numberic dataset by indicating the % of the dataset w/ a lesser value

A

Percentile

30
Q

Caculated by divising an ordered set of data into 100 equal parts

A

Percentile

31
Q

A measure of the asymmetry of a distribution
Horizontal imbalance

A

Skewness

32
Q

A distribution is asymmetrical:

A

When its left and right side are not mirror images

33
Q

Right skewness

A

Positive distribution

34
Q

Left skewness

A

negative distribution

35
Q

Zero skewness

A

0

36
Q

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

A

Kurtosis

37
Q
A

JDL (8 decks)

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