2.2 Characteristics Of Data

The variable "Colour of stick tape used" is qualitative because it represents a characteristic or attribute that cannot be measured numerically. It is a categorical variable that describes the type or color of stick tape used by a hockey player.

The variable "Stride length" can be considered continuous because it can take on any value within a certain range. It is a measurement of the length of each stride taken by a hockey player while they are skating, and can vary from player to player. In contrast, the other variables mentioned are not continuous. The "Number of goals scored" and "Number of Stanley Cups won" are discrete variables that can only take on whole number values, while the "Colour of stick tape used" is a categorical variable with a limited number of options.

The variables mentioned in the question, such as speed, shot strength, goal scored, and +/- rating, are all quantitative because they can be measured and expressed numerically. Additionally, some of these variables, such as speed and shot strength, are continuous as they can take on any value within a certain range. On the other hand, variables like goals scored and +/- rating are discrete as they can only take on specific, separate values.

A longitudinal sample study would be the most appropriate for this thesis question. This type of study involves collecting data from the same group of student athletes over a period of time, in this case, the school year. By tracking and comparing their grades at different points throughout the year, researchers can determine if there are any changes or patterns in their academic performance. This study design allows for a more in-depth analysis of how the grades of student athletes evolve over time.

It is better to take a sample rather than a census in scenarios where the population is too large or spread out, making it impractical or time-consuming to collect data from every individual. In the given options, both testing light bulbs and determining the termite population require observing a large number of items or organisms, which would be more efficiently done through sampling rather than conducting a census.

A longitudinal study that takes a census of the counties where the crop is grown would be the most appropriate because it allows the researcher to collect data over a period of time and observe how the price of the crop varies with the weather. By taking a census of all the counties where the crop is grown, the researcher can obtain a comprehensive understanding of how the crop price is influenced by different weather conditions across the country. This type of study design would provide more accurate and reliable results compared to a cross-sectional study that uses a sample of counties or takes a census at a single point in time.