A poor manager. You cannot manage anything successfully if you only look in one direction or use data from a single source. A successful manager should know everything about his area of responsibility by being involved in the process. Armchair managers rarely make important decisions without relying on someone Else's knowledge and when things go wrong, you know what, flows downhill.
dialectical inquiry
A career objective for a manager may be to find a job that will challenge their analytical skills. They can use this to find a position in firms they have never worked for.
No, this sampling plan does not result in a random sample. Since the manager only speaks to the 25 employees who attended a specific meeting, the sample is not representative of the entire employee population, as it may exclude those who were absent or not invited to the meeting. A random sample would require selecting employees from the entire workforce without bias, ensuring every individual has an equal chance of being included.
To address the manager's concern, the sample data on the 100 individuals should be analyzed to determine peak arrival times, service durations, and customer wait times. This information can help identify specific bottlenecks and assess whether the current single-window system meets the growing demand. Based on the findings, potential solutions could include increasing service windows, extending hours, or implementing an appointment system to enhance efficiency and customer satisfaction.
Some sample exit interview questions to gather feedback from departing employees may include: What factors influenced your decision to leave the company? How would you rate your overall experience working here? Did you feel supported by your manager and colleagues during your time here? What suggestions do you have for improving the workplace culture or environment? Were there any specific challenges or issues that you faced during your time here? What could the company have done differently to retain you as an employee? Do you have any recommendations for how we can better support and develop our employees in the future?
dialectical inquiry
Biased generalization
A generalization is likely correct when it is supported by a large sample size or a diverse range of examples. Additionally, if the generalization can be logically explained and is consistent with existing knowledge or trends, it is more likely to be correct. Testing the generalization through experimentation or further research can also help validate its accuracy.
Representative generalization supported on page 338; last para
A hasty generalization occurs when a conclusion is drawn from an insufficient or unrepresentative sample. For example, claiming that all teenagers are irresponsible based on a few instances of reckless behavior is a hasty generalization. This type of reasoning overlooks the diversity and complexity of the broader population, leading to inaccuracies and stereotypes. Ultimately, it can result in unfair judgments and misconceptions.
no
what information about the sample of a mean not provide
yes
An inductive generalization takes a sample of a population and makes a conclusion regarding the entirepopulation.Inductive Generalizations take the form..X percent of observed Fs are GsthereforeX percent of all Fs are GsFor example, an experiment may test the effects of a drug on lab mice. They might reason..80% of observed mice die when given the drug.therefore80% of all mice die when given the drug.The argument's strength depends on the sample. A sample that is not representative of the population is called a biased sample.
They hope to generalize the findings of their studies to populations of interest. When a sample is not representative of the generalization of the population it may be inaccurate.
A simple random sample is a method of selecting a sample where the probability of any particular member of the population being part of the sample is the same for all members of the population.
The argument contains the fallacy of hasty generalization, where Abbey makes a broad generalization about all rich people based on a limited sample size of five individuals. This does not provide sufficient evidence to support his claim.