why is data so important in statistics

want summary statistic on gender, age group, weight, and weight loss

Trixie

are you asking question or looking for Solution

Arun

1st convert gender and group to factor than use summary function It will give mean median and mode with other details

Arun

its a bit complicated could u bring it to my level of under standing

Trixie

u know the question was put in a tabular form where we were to find the variable type, summary statistics and graph type of the given variables that's the gender,age group, weight and weight loss

Trixie

if you see, gender and group are not numerical due to which they will not give you correct statistics

Arun

how you denote gender m or f

Arun

these are not numerical so you have to convert they as f=1; m=2; t=3 same thing you have to do with group or any variable which is character else you should drop them

Arun

from your calculation

Arun

so pls why is data important in statistics

Trixie

not only data correct data is imp

Arun

statistics works on data only

Arun

without data you can not summarize, can not predict future, can not establish relationship between two and more variables, can not prepare reports and make decisions on it

Arun

so I'll give example. suppose you want to open a restaurant and you have to choose one best location out of 5. then how you will decide which location is best for you

Arun

awww thank you pls

Trixie

pls I want a brief note on observation, survey and experimentation way of obtaining data

Trixie

please Tell me difference parameters and non parameter

Abdiwahab

can you tell me about the scopes of statistics?

Minhal

plzzz answer me anyone .

Minhal

Methods of Collecting Data
Observation
Observational studies allow researchers to document behavior in a natural setting and witness events that could not be produced in a lab.

Arun

Key Points
Observation differs from most other forms of data collection in that the researcher does not manipulate variables or directly question participants.
The advantages of observation include observing natural behavior, refining hypotheses, and allowing for observation of behavior that canno

Arun

be produced in an artificial environment for ethical or practical reasons.
The disadvantages of observation are that these studies do not produce quantitative data, do not allow for cause and effect statements, may be very time consuming, and can be prone to researcher bias.

Arun

Key Terms
observational research: Research focusing on the observation of behavior outside of a laboratory setting.
external validity: In research, whether or not study findings can be generalized to real world scenarios.

Arun

Surveys and Interviews
Surveys are a low-cost option for gathering a large amount of data, but they are also susceptible to reporting bias.

Arun

Key Points
The survey method of data collection is likely the most common of the four major research methods.
The benefits of this method include low cost, large sample size, and efficiency.

Arun

The major problem with this method is accuracy: since surveys depend on subjects’ motivation, honesty, memory, and ability to respond, they are very susceptible to bias.
A researcher must have a strong understanding of how to properly frame survey questions in order to gather reliable and relevant

Arun

Key Terms
reliability: The degree to which a measure is likely to yield consistent results each time it is used.
validity: The degree to which a measure is actually assessing the concept it was designed to measure.
survey: A method for collecting qualitative and quantitative information about ind

Arun

individuals in a population.

Arun

Interviews
Interviews are a type of qualitative data in which the researcher asks questions to elicit facts or statements from the interviewee. Interviews used for research can take several forms:

Arun

Informal Interview: A more conversational type of interview, no questions are asked and the interviewee is allowed to talk freely.
General interview guide approach: Ensures that the same general areas of information are collected from each interviewee. Provides more focus than the conversational ap

Arun

approach, but still allows a degree of freedom and adaptability in getting the information from the interviewee.
Standardized, open-ended interview: The same open-ended questions are asked to all interviewees. This approach facilitates faster interviews that can be more easily analyzed and compared

Arun

Closed, fixed-response interview (Structured): All interviewees are asked the same questions and asked to choose answers from among the same set of alternatives.

Arun

experiments
An experiment involves the creation of a contrived situation in order that the researcher can manipulate one or more variables whilst controlling all of the others and measuring the resultant effects.

Arun

Boyd and Westfall1 have defined experimentation as:
"...that research process in which one or more variables are manipulated under conditions which permit the collection of data which show the effects, if any, in unconfused fashion."

Arun

Experiments can be conducted either in the field or in a laboratory setting. When operating within a laboratory environment, the researcher has direct control over most, if not all, of the variables that could impact upon the outcome of the experiment

Arun

When experiments are conducted within a natural setting then they are termed field experiments. The variety test carried out by United Fruits on their Gros Michel and Valery bananas is an example of a field experiment.

Arun

parameter
Parameters are factors or limits which affect the way that something can be done or made

Arun

Minhal didny get your question, can you please elaborate more

Arun

pls can u use mean n mode at the statistical summary pls

Trixie

yes, statistical summary itself gives all value

Arun

but u didn't tell me the advantage and disadvantage of the experimental method

Trixie

but you didn't tell me the advantage and disadvantage of experimental method

Trixie

What are the 5 steps of hypothesis testing?

5 steps of hypothesis testing

Sixolisiwe

Make guesses (e.g., customers will leave if we raise our rates)
State the null H0 and alternative H1 hypotheses (e.g., H0: there is no correlation) and alpha
Select the sampling distribution and specify the test statistic
Compute the test statistic
Make a decision and interpret the results

Ara

.Five Steps in Hypothesis Testing:
1_Specify the Null Hypothesis.
2_Specify the Alternative Hypothesis.
3_Set the Significance Level (a)
4_Calculate the Test Statistic and Corresponding P-Value.
5_Drawing a Conclusion.

Rachel

.Econometric Results uses Multiple Regression for the basis of looking at number of casual factors (independent χ Variables) such as Employment, being Female etc., to test for any relationship with the dependent γ Variable Wages, in order to find any evidence to support the Alternative Hypothesis(Ha

Rachel

.Alternative Hypothesis (H1 or Ha) of Wage Differentials or in the extreme case, if the strength of relationship is strong enough between the dependent γ Variable, and multiple χ Variables, suggesting evidence for the Null Hypothesis ( Ho) that Wage Discrimination may exist.

Rachel

.The Significance Level which is also the Critical Value gives the maximum allowable probability of making a Type I error – the Significance Level value of which is decided upon before the data sample is collected and analysed, as a guide to avoid or control making a Type I error.

Rachel

Type I Error occurs when the Null Hypothesis (Ho) is not accepted when in reality the Null Hypothesis is true. A Type II Error however, occurs when one fails to reject the Null Hypothesis when in reality, the Null Hypothesis (Ho) is not true.

Rachel

.The #P-Value measures the likelihood of getting the sample results if the Null Hypothesis were true, and could be defined as the smallest level of significance (observed level of significance) at which the Null Hypothesis will be rejected, assuming the Null Hypothesis (Ho) is true.

Rachel

.In most cases, the research attempt is to find support for the Alternative Hypothesis (Ha or H1). Thus, the smaller the P-Value, the more the (the father out the #Test-Statistics is on the Standard Normal Distribution Diagram, and the more confident the researcher can be about rejecting the Null H

Rachel

.#Test-Statistics is on the Standard Normal Distribution Diagram, and the more confident the researcher can be about rejecting the Null Hypothesis (Ho) in support for the Alternative Hypothesis (H1 / Ha).

Rachel

.The #P-Value is less than the Critical Values (Significance Level) of 1% (0.01), 5% (0.05), and 10% (0.10) given in Table (1) in the Appendix, means the Null Hypothesis (Ho) that there is Wage Discrimination is not reflective of the population or equal to the Mean of the Population

Rachel

.Mean of the Population(data sample of Sample Mean distribution of the Population ) which confirms that the Researcher Rejects the Null Hypothesis (Ho) and Accepts the (Alternative Hypothesis).

Rachel

.See ISBN 1537512757 ; link : https://smile.amazon.co.uk/Winston-Chellie-Economics-TheBachelor-questions/dp/1537512757/ref=mp_s_a_1_1?keywords=Rachel+Adeniji&qid=1572318698&sr=8-1

Rachel

see publication ' Winston and Chellie by Rachel Adeniji '

Rachel

correction, dependent x variables such as Employment, being Female; dependent y variable Wages

Rachel

correction, Wage Differentials such as Employment, Region affecting Wages; Wage Discrimination such as being Female or Ethnicity affecting Wages

Rachel

correction_, linear regression/equation is computed as
y=mx + c or y=m • x1+x2+x3+c where independent x variables eg Employment x1, Female x2 , Ethnicity x3, and dependent y variable Wages

Rachel