BIO 11.1 24.L (EXERCISE 2)

categorical (qualitative)
numerical (quantitative).

Observed data or variables can be:

Categorical data
Nominal
Ordinal

• are derived from qualitative observations and may be divided into distinct groups.

  • N_

  • O_

numerical data
Discrete
Continuous

• are obtained from objective measurements and may be D_ or C_.

Nominal data

• are classified into groups that do not exhibit inherent ranking or

  ordering.

Ordinal data

• are grouped into categories that exhibit ranking or ordering.

Discrete numerical data

• can be recognized as counts or frequencies in integers or whole numbers.

Continuous data

• on the other hand, are taken from measurements on a scale.

• EXAMPLE:

  • Dimensions of Height,

  • Weight, and

  • Length

Inferences
Randomly sampled
Uniformly treated
Central tendency
Dispersion
Descriptive statistics.

Describing Quantitative Data:

• The goal of measurements is to make _ about a population.

• However, it is often logistically impossible to take measurements from all individuals in a population, thus only a sample of that population is studied.

• To make accurate predictions or generalizations about the population, it is desired that this subset is a good representation of the whole, thus measures are taken to ensure it is of sufficient size, and that its members are _ or are _ or controlled.

• After gathering your data from a sample, you may need to make sense of the values by using measures of C_ t_ and D_. These are often referred to as _.

Mode
Median
Mean

What is the difference between the measures of central tendency and the measures of dispersion?

• The measures of Central tendency include the _, the _ and the _.

Range
Variance
Standard deviation

What is the difference between the measures of central tendency and the measures of dispersion?

• The measures of dispersion include _, _, and _.

Table
Graph
Bar graphs
Line graphs
Scatter diagrams

Presenting Quantitative Data:

• There are two main formats to present quantitative data, namely, using a _ or using a _. Each should be presented with a properly written title.

• There are several different types of graphs that can be used to present quantitative data including

  • B_,

  • L_, and

  • S_.

Histogram

• Another unique type of graph is the _.

• This is a way to visualize the distribution of values in a sample.

• It is similar to a bar graph, where each bar represents a class or a bin of grouped continuous data.