Yes--these two terms mean essentially the same thing. There might be variation among practicing statisticians and researchers (perhaps geographically, with those in the U.S. preferring the phrase "inferential" and those in other countries perhaps more likely to use "inductive"). The goal of inferential statistics is to make a broader statement about a large group from a small subset of that group--and the phrase "inductive reasoning" refers to making a broader generalization (that is, an inference) from a series of observations. Thus, these two phrases refer to the same thing.
yes
SE stands for ''standard error'' in statistics. Thanx Sylvia It is the same as the standard deviation of a sampling distribution, such as the sampling distribution of the mean.
The group of individuals used to represent a population is called the sample. It should have the same statistics as the population, though be of a smaller size.
same as grouped data i.e. (upper limit+lower limit)/2
If repeated samples are taken from a population, then they will not have the same mean each time. The mean itself will have some distribution. This will have the same mean as the population mean and the standard deviation of this statistic is the standard deviation of the mean.
yes
The unit of measurement for inductive reactance (XL) is the ohm.
It means that every member of the population has the same probability of being included in the sample.
A sampling distribution describes the distribution of a statistic (such as the mean or proportion) calculated from multiple random samples drawn from the same population. It provides insights into the variability and behavior of the statistic across different samples, allowing for the estimation of parameters and the assessment of hypotheses. The central limit theorem states that, given a sufficiently large sample size, the sampling distribution of the sample mean will approximate a normal distribution, regardless of the population's distribution. This foundation is crucial for inferential statistics, enabling conclusions about a population based on sample data.
Inductive reactance does NOT have it own sign or symbol. Rather, it uses Ohms as a quantifier. But Capacitive reactance ALSO uses Ohms as a quantifier. Fortunately, 1 Ohm of Inductive reactance is cancelled by 1 Ohm of Capacitive reactance at the same frequency of measurement.
SE stands for ''standard error'' in statistics. Thanx Sylvia It is the same as the standard deviation of a sampling distribution, such as the sampling distribution of the mean.
There is no problem using a generator to run more inductive load so long as the generator capacity can supply the needed power to the inductive loads. The inductive loads should not be switched on at the same time but there should be a little delay before another load is switched ON as inductive loads draw more power at start ON. The power factor of the inductive loads also affect the generator, hence for safe operation a power factor that is approaching 1 is desirable. Ogu Reginald Ekene
False. While computers can perform tasks that mimic inductive reasoning, such as pattern recognition and machine learning, they do not truly understand or reason in the same way humans do. Their processes are based on algorithms and statistical analysis rather than the intuitive leap that characterizes human inductive reasoning. Thus, while they can simulate aspects of inductive reasoning, they do not possess the capability in the human sense.
A representative sample is one where the statistics of the sample are the same as the statistics for the parent population.
Inductive reactance is a resistance by inductors to the change of current flow, and is dependent on the frequency at which the current oscillates. DC current flows in only one direction so an inductor's impedance remains the same.
Deductive and inductive reasoning are both methods of logical thinking used to draw conclusions. They both involve making observations, forming hypotheses, and reaching conclusions based on evidence. However, deductive reasoning moves from general principles to specific conclusions, while inductive reasoning moves from specific observations to general conclusions.
Yes, it is possible to obtain three different values for the same statistic from three different samples of the same size drawn from a population. This variability occurs due to sampling error, which is the natural fluctuation in sample statistics due to the random selection of individuals. Each sample may capture different subsets of the population, leading to variations in calculated statistics such as the mean, median, or standard deviation. Hence, different samples can yield different estimates, even though they come from the same population.