Week 2

Question 1

what is data visualisation?

Answer 1

the process of displaying data often in large quantities in a meaningful fashion to provide insights that will support better decisions.

Question 2

what are the three general principles for visualisation?

Answer 2

• design and layout matter
• avoid clutter
• there should be a reason behind using colours and they should be used effectively

Question 3

what is dashboard?

Answer 3

a visual representation of a set of key business measures

Question 4

what is a column and bar chart?

Answer 4

• column chart is vertical type of bar charts
• bar charts are a horizontal type of bar charts
• A clustered column chart compares values across categories using vertical rectangles
  -a stacked column chart displays the contribution of each value to the total by stacking the rectangles
• a 100% stacked column chart compares the percentage that each value contributes to a total.
• Column and bar charts are useful for comparing categorical or ordinal data, for illustrating differences between sets of values,

Question 5

what is a line chart?

Answer 5

it provides a useful means for displaying data over time

Question 6

what is a pie chart

Answer 6

displays the relative proportion of each data source to the total. it partitions the circle into pie shaped areas showing the relative proportion

Question 7

what is an area chart?

Answer 7

combines the feature of a bar chart with those of the line charts, they present more information than pie of line charts

Question 8

what is a scatter charts?

Answer 8

it shows the relationship between two variables. to construct one, we need observations that consist of pairs of variables

Question 9

what is a bubble chart?

Answer 9

a type of scatter chart in which the size of the data marker corresponds to the value of a third vaiable

Question 10

what is a statistic?

Answer 10

is a summary measure of data

Question 11

what is descriptive statistics?

Answer 11

refers to methods of describing and summarising data using tabular, visual and quantitative techniques

Question 12

what is a frequency distribution?

Answer 12

a table that shows the number of observations in each of several nonoverlapping groups

Question 13

what is a histogram?

Answer 13

a geographical depiction of a frequency distribution for numerical data in the form of a column chart

Question 14

how do you form a frequency distribution?

Answer 14

1. the number of groups
2. the width of each group
3. the upper and lower limits of each group

Question 15

what is cumulative relative frequency?

Answer 15

The cumulative relative frequency represents the proportion of the total number of observations that fall at or below the upper limit of each group.
- A tabular summary of cumulative relative frequencies is called a cumulative relative ­frequency distribution.

Question 16

what is cross tabulation?

Answer 16

a tabular method that displays the number of observations in a data set for different subcategories of two categorical variables

Question 17

what is a population?

Answer 17

consists of all items of interest for a particular decision of investigation

Question 18

what is a sample?

Answer 18

a subset of a population

Question 19

what is the mean?

Answer 19

the sum of the observation divided by the number of observations

Question 20

what are outliers?

Answer 20

observations that are radically different from the rest

Question 21

what is the median?

Answer 21

the measure of location specifies the middle value when the data are arranged from least to the greatest

Question 22

what is the mode?

Answer 22

observation that occurs the most

Question 23

what is the mdirange?

Answer 23

thw average of the greatest and least values in the data set

Question 24

what is the range?

Answer 24

the difference between the maximum and minimum value in the data set

Question 25

What is interquartile range?

Answer 25

the difference between the first and third quartiles

Question 26

what is the variance?

Answer 26

the composition depends on all the data. the larger the variance, the more the data are spread out from the mean and the more variability one can expect in the observations.

Question 27

what are the empirical rules?

Answer 27

• The ­percentages are generally much higher than what Chebyshev’s theorem specifies. These are reflected in what are called the empirical rules :
  1. Approximately 68% of the observations will fall within one standard deviation of the mean, or between x - s and x + s .
  2. Approximately 95% of the observations will fall within two standard deviations of the mean, or within x (plus or minus) 2 s .
  3. Approximately 99.7% of the observations will fall within three standard deviations of the mean, or within x (plus or minus) 3 s.

Question 28

what is a standardised value?

Answer 28

also known as the z -score , provides a relative measure of the distance an observation is from the mean, which is independent of the units of measurement.

Question 29

what is the coefficient variation (CV)?

Answer 29

The coefficient of variation (CV) provides a relative measure of the dispersion in data relative to the mean.
- The coefficient of variation provides a relative measure of risk to return. The smaller the coefficient of variation, the smaller the relative risk is for the return provided. The reciprocal of the coefficient of variation, called return to risk , is often used because it is easier to interpret. That is, if the objective is to maximize return, a higher return-to-risk ratio is often considered better.

Question 30

what is skewness?

Answer 30

• it describes the lack of symmetry of data.
  Those that tail off to the right, like this example, are called positively skewed ; those that tail off to the left are said to be negatively skewed.
• The coefficient of skewness (CS) measures the degree of asymmetry of observations around the mean.

Question 31

what is proportion?

Answer 31

Statistics such as means and variances are not appropriate for categorical data. Instead, we are generally interested in the fraction of data that have a certain characteristic. The formal statistical measure is called the proportion , usually denoted by p.
- they should be between 0 and 1.

Question 32

what is covariance?

Answer 32

the measure of the linear association between two variables X and Y

Question 33

what is correlation?

Answer 33

measure of the linear relationship between two variables X and Y which doesnt depend on the units of measurement.
- its measured by the correlation coefficient

Question 34

what is probability?

Answer 34

the likelihood that an outcome will occur

Question 35

what is the sample space?

Answer 35

the collection of all possible outcomes of an experiment

Question 36

what are the two basic factors that govern probability?

Answer 36

1. the probability associated with any outcome must be between 0 and 1
2. the sum of the probabilities over all possible outcomes must be 1.0

Question 37

what is an event?

Answer 37

a collection of one or more outcomes from a sample space
1. The probability of any event is the sum of the probabilities of the outcomes that comprise that event.
2. If A is any event, the complement of A , denoted A sample space not in Ac, consists of all outcomes in the sample space NOT in A.
- The probability of the complement of any event A is P (Ac) = 1 - P(A) .

Question 38

what is a random variable?

Answer 38

A numerical description of the outcome of an experiment. Formally, a random variable is a function that assigns a real number to each element of a sample space.
- they can be discrete or continuous and they could be known or empirical

Question 39

what is discrete and continuous variable?

Answer 39

• A discrete random variable is one for which the number of possible outcomes can be counted.
• A continuous random variable has outcomes over one or more continuous intervals of real numbers.