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What else can I help you with?
Why are sample used in statistics?
Because a sample is information obtained from the population that will be used in hypothesis testing. WER 1.19.2011 Samples are used to save time and money when the population is large and when the units must be destroyed to gain information.
What is the studying a part in order to gain information about the whole?
Sampling
How important is statistics in medicine?
Incredibly important ! All clinical practice is based on statistics. Would you implement an intervention (ie a new drug) if you had no proof that it worked ! In medical practice we gain knowledge and make decisions based on knowledge gained though research.
Why tourism has to be measured and the importance of tourism statistics?
In the economies of some countries tourism is a principal source of foreign exchange. To avoid losses of this source it is important to gather statistics for study. In other countries it may be suspected that tourism could be beneficial to the economy. Here, statistics can be gathered as the basis for making projections. In some tourist destinations, notably Paris, it has been observed that although many people visit, little of their money is spent there. Statistics could be gathered in order to attempt to learn how to gain more benefit from these visits.
Merit and demerit of primary and secondary data?
PRIMARY DATA MERITS 1. it gives valid information 2. you can observe finer nuances as in the case of interview or observation method 3. as in questionnaire, the anonimity of respondent is preserved DEMERITS 1. it can be difficult to gain access to the sample 2. the sample may behave unnaturally in the presence of the interviewer 3. personal bias may affect the outcome 4. it can be time consuming SECONDARY DATA MERITS 1. a variety of information 2. variety of opinions 3. in depth information 4. time saving DEMERITS 1. the data may be inaccurate 2. the data may be outdated 3. personal bias of researcher may affect the result 4. the information may not always be relevant
What is inferential statisics?
inferential statistics allows us to gain info about a population based on a sample
Do you gain or lose information when you use statistics to reduce a population to a few characteristic number?
You lose information.
Why are sample used in statistics?
Because a sample is information obtained from the population that will be used in hypothesis testing. WER 1.19.2011 Samples are used to save time and money when the population is large and when the units must be destroyed to gain information.
Do you lose or gain information when you use statistics to reduce a population to a few characteristic numbers?
you lose information!becoz you can nearly exact the data based on the charateristic numbers
Do you gain or loose information when you use statistics to reduce a population to a few characteristic numbers?
When you use statistics to reduce a population to a few characteristic numbers, you are simplifying the data by summarizing it into key measures like mean, median, and standard deviation. While you may lose some degree of detail and complexity in the process, you gain a clearer understanding of the population's central tendencies and variability, making it easier to draw insights and make informed decisions from the data.
What is the difference between sample and example?
Definition of example is one (as an item or incident) that is representative of all of a group or type.Similarly, a definition of sample is1) a representative part or a single item from a larger whole or group especially when presented for inspection or shown as evidence of quality.Another definition of sample is2) a finite part of a statistical population whose properties are studied to gain information about the whole.The difference being that an example is typically one item and a sample is one or more items.
What is the population of Gain Capital?
Gain Capital's population is 380.
What is Hy-Gain's population?
Hy-Gain's population is 75.
How do you do inferential statistics?
Inferential statistics is the practice of sampling large sets of data (usually at random) to gain information about the population as a whole. Sampling is used because measuring everything in the population can consume too many resources (time, money, etc.) I suggest looking at these topics for an intro into inferential statistics: 1) Sampling (random, stratified, etc) 2) Mean, variance/standard deviation, median, and mode 3) Data distributions 4) Confidence intervals 5) T-tests 6) Analysis of variance 7) Trend analysis (regression) 8) Association analysis ... and many more!
WHAT IS INFORMATION AND LIST AND EXPLAIN SOURCE OF INFORMATION?
Information is data that has been processed and given meaning. Sources of information include books, academic journals, websites, interviews, surveys, and databases. These sources provide various types of information such as facts, statistics, analyses, and opinions to help individuals gain knowledge and understanding on a particular topic.
What is importance of statistics in geography?
Statistics play a crucial role in geography by providing tools for data analysis, interpretation, and decision-making. Geographic information systems (GIS) rely heavily on statistical techniques to analyze spatial data and identify patterns and relationships. Statistics help geographers understand trends, make predictions, and draw meaningful conclusions about spatial phenomena such as population distribution, land use, and environmental changes. Overall, statistics in geography help researchers gain insights into complex geographical processes and inform evidence-based decision-making in areas such as urban planning, resource management, and environmental conservation.
Definition of sample profiling?
Sample profiling involves analyzing a subset of the data (sample) to gain insights into the characteristics and behavior of the entire population. This technique is commonly used in market research, data analysis, and data mining to make inferences and predictions about a larger group based on the sample data. It helps to understand the key attributes, trends, and patterns to make informed decisions.
