Time series data is concerned with the implications of time in accordance of a data set. Cross-sectional data is similar, however it is lacking the aspect of time.
Identify a qualitative and quantitative variable in each data set.
Qualitative Time Series: Birthrate over a period of time for a school district
Qualitative Cross-Sectional: Country of Origin
Quantitative Time Series: Income over a period of time
Quantitative Cross-Sectional: Hours worked in a particular week
Identify a discrete and continuous variable in each data set
Discrete Time Series: Class attendance over a week long period
Discrete Cross-Sectional: Number of products sold today
Continuous Time …show more content…
Interpreting the recoded numbers as actual values would result in information that means nothing and therefore wasted effort.
P1.4: Discrete Data: Number of workers present; Continuous Data: Time needed to complete an exam
P1.11: Either Freshman, Junior, or Senior
P1.12: Either have a job, don’t have a job, or your retired
P1.15: Qualitative data is the observation of qualities while Quantitative data are observations of quantities; Ex: Gender for qualitative and income for quantitative. This question highlights the key information researchers want to know about the data.
MBA Admissions: A school in the northern eastern United States is concerned with the recent drop in female students in its MBA program. It decides to collect data from the admissions office on each applicant, including: sex of each applicant, age of each applicant, whether or not they were accepted, whether or not they attended and the reason for not attending (if they did not attend). The school hopes to find commonalities among the female accepted students who have decided not to attend the business program.
Identify the cases
Each applicant in the MBA