Answer:
A cross-sectional study
Explanation:
Cross-sectional research in psychology is defined as using a variety of people who differ in the variable of interest but carries other characteristics as well, including educational background, ethnicity, socioeconomic status, etc. It is often used by a researcher who studies developmental psychology. it is used for population-based surveys and to assess the prevalence of disease. These studies are usually inexpensive and relatively faster.
Answer:
D
Explanation:
The definition of n! is n x (n-1) x (n-2) x ... x 1.
So 10! = 10 x 9 x 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 i.e. D.
Answer:
a. It aids in the comprehension of the existing status of the business or process.
b. No, it not possible to we think of analytics without data
Explanation:
a. How do you describe the importance of data in analytics?
Data analytics can be described as the art and science of extracting useful information from data.
It aids in the comprehension of the existing status of the business or process and serves as a solid foundation for forecasting future results. Businesses can use data analytics to better comprehend the present market situation and adjust their processes or trigger the need for new product development to meet market demands.
b. Can we think of analytics without data?
No, it not possible to we think of analytics without data. This is because the raw material that is employed for analytic is data. Therefore, there would be nothing like analytics when there is no data.
Answer:
Mainframes
Explanation:
<em>Mainframes</em> are typically identified by their big size, high reliability, and massive processing power. One mainframe can replace a lot of small servers (running to hundreds) and work efficiently. Mainframes emphasize throughput computing because they can manage many high volume input/output (I/O) and can run multiple instances of Operating Systems (OS) concurrently.
Mainframes are mostly used by large organizations that carry out activities that require a high volume of data processing. Some of these data can be transaction processing, enterprise resource analysis, customer and industry stats, census among others.
Due to their reliability and stability, mainframes can run for a long time without any form of interruption and are very useful in cloud data centers.