Lesson 1: Data Collection and Presentation

Question 1

is the science of collecting, organizing, analyzing, and interpreting numerical data to assist in making effective decisions

Answer 1

Statistics

Question 2

Uses the data to provide descriptions of the population, either through numerical calculations, graphs and tables.

Answer 2

Descriptive Statistics

Question 3

makes inferences and predictions about a population based on a sample of data taken from the population in question.

Answer 3

Inferential Statistics

Question 4

is a collection of all possible individuals, objects, or measurements of interest

Answer 4

Population

Question 5

is a portion, or part of the population of interest

Answer 5

sample

Question 6

the total number of things in the sample

Answer 6

sample size

Question 7

Types of Variables

Answer 7

Quantitative and Qualitative

Question 8

examples of Qualitative Variables

Answer 8

Brand of PC, Marital status, Hair color

Question 9

Types of Quantitative variables

Answer 9

Discrete and Continuous

Question 10

types of discrete variables

Answer 10

Children in a family, strokes on a golf hole, TV sets owned.

Question 11

Types of continuous variables

Answer 11

amount of income tax paid, weight of a student, yearly rainfall in Tampa, FL

Question 12

Result when a single variable is measured on an experimental unit

Answer 12

Univariate data

Question 13

result when two variables are measured on a single experiment unit

Answer 13

Bivariate data

Question 14

result when more than two variables are measured

Answer 14

multivariate data

Question 15

Qualitative data are popularly summarized using

Answer 15

Bar graph and Pareto chart

Question 16

is a simple technique
for prioritizing possible changes by
identifying the problems that will be
resolved by making these changes By
using this approach, you can prioritize
the individual changes that will most
improve the situation

Answer 16

Pareto Analysis

Question 17

Quantitative data are commonly summarized using

Answer 17

Histogram and dotplots

Question 18

What are the shapes of distribution?

Answer 18

Bell-shaped, Uniform, Right-skewed, Left-skewed, Bimodial, U-shaped

Question 19

Bivariate quantitative data are summarized using

Answer 19

scatterplots

Question 20

Multivariate quantitative data are summarized using

Answer 20

Scatterplots

Question 21

Data collected over time are generally summarized using

Answer 21

Time-series plots

Question 22

the data value located exactly at the centermost position when the data set is arranged in order.

Answer 22

Median

Question 23

TRUE or FALSE: The median may be preferred to the mean if the data are highly skewed.

Answer 23

True

Question 24

the most frequently occurring data value

Answer 24

Mode

Question 25

If all the elements in the data set have the same frequency of occurrence, then the data set is said to have.

Answer 25

No mode

Question 26

If the data set has one value that occurs more frequently than the rest of the values, then the data set is said to be.

Answer 26

unimodal

Question 27

If two elements of the data set are tied for the highest frequency of occurrence, then the data set is said to be

Answer 27

bimodal.

Question 28

measures the spread of the middle 50% of an ordered data set.

Answer 28

Interquartile Range

Question 29

largest value – smallest value

Answer 29

Range

Question 30

a way to measure how far a set of numbers is spread out.

Answer 30

Variance

Question 31

the average amount of variability in your dataset

Answer 31

Standard Deviation

Question 32

means that most of the numbers are close to the average.

Answer 32

Low standard Deviation

Question 33

means that the numbers are more spread out.

Answer 33

High standard deviation

Question 34

measures the distance between an observation and the mean, measured in units of standard deviation.

Answer 34

Z-score

Question 35

divide a data set into 100 equal parts. It is simply a measure that tells us what percent of the total frequency of a data set was at or below that measure.

Answer 35

Percentiles

Question 36

As the name suggests, quartiles break the data set into 4 equal parts.

Answer 36

Quartiles

Question 37

steps in in constructing a frequency distribution table

Answer 37

1. Find the range.
2. Identify the number of classes using sturges rule
3. Determine the interval size by dividing the range by the desired number of classes.
4. Determine the class limits of the class intervals.
5. Determine the midpoints by averaging the lower and the upper class limits of each class.
6. Tally the frequencies for each interval then get the sum.

Question 38

these are numbers defining the class consisting of the end numbers called the class limits (upper limit and lower limit)

Answer 38

Class Interval

Question 39

shows the number of observations falling in the class

Answer 39

Class Frequency (f)

Question 40

these are the so-called “true class limits”

Answer 40

Class Boundaries

Question 41

– middle value of the lower class limit of the class and the upper class limit of the preceding class

Answer 41

Lower Class Boundary (LCB)

Question 42

– middle value between the upper class limit and the lower limit of the next class

Answer 42

Upper Class Boundary (UCB)

Question 43

the difference between two consecutive upper limits or two consecutive lower limits

Answer 43

Class size

Question 44

– midpoint or the middle value of a class interval

Answer 44

Class Marks (CM)

Question 45

what are the MEASURES OF CENTER OF DATA DISTRIBUTION

Answer 45

Mean, Median, Mode

Question 46

what are the MEASURES OF VARIABILITY

Answer 46

RANGE & INTERQUARTILE RANGE, VARIANCE, and STANDARD DEVIATION

Question 47

SIGNIFICANCE OF STANDARD DEVIATION

Answer 47

Chebyshev’s Theorem and The Empirical (Normal) Rule

Question 48

what are the MEASURE OF RELATIVE STANDING

Answer 48

Z-SCORE