Health State Statistics Analysis
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Question A
A restatement is mentioned as a review and publication of a business’s earlier issued financial report. The determination is to advise report operators of erroneous data in earlier released statements and offer modified documents. Statement workers frequently make significant investment decisions built entire financial report as demonstrated by low income acquired from health state
H0: µ = 550
H1: µ 6= 550
H0: Null Hypothesis: average = 6%
H1: Alternative Theory: mean > 6%
95% confidence level on income level on health conditions lying on two standard deviations within the income level. Thus, normal distribution within essential limit statement within sample dataset letting one in establishing 5% as a significance level
100-5=95%
| N | Mean | Standard deviation | Standard error mean | |
| Figure on learners on health state | 450 | 100 | 1.54 | 0.305 |
Low income on health
| Model | R | R Square | Readjusted R Square | Standard error Estimate |
| 2.00 | 0.417 | 0.111 | 0.305 | 0.00 |
Ninety-five percent Confidence intermissions continually quantified as a proportion, where example, was measured as a 95% confidence share. The self-assurance level expresses key statistics on health conditions. Relieving model figures and Z rating whereby 95% confidential scope quantified concerning low income in health state,
95%=122.4+1.971(20.20/ (305^1/2)
=122.4.4+0.166=124.43
122.4-0.0166=121.45
100-95=5
5%=0.05
p>0.05
Thus, it considered essential to accept the null hypothesis
Question B
Generally, Y considered a variable dependent on X, while X, mentioned and quantified as an independent variable.
Significant Statistics
| N | Mean | Standard deviation | Standard error mean | |
| Number of researcher s | 98 | 115 | 1.69 | 0.120 |
y = f(x) = 5x + 6
The function expresses that, y, as a dependent variable, depending on x, and independently adjustable. Therefore, the independent variable, x, could have diverse values. The time x changes y also does the same. The health state income mentioned having readjusted square of 0.714, having a quantified model (Plonsky, & Oswald, 2017).
Question C
95% of statistics
122.4.4+0.166=124.43
122.4-0.0166=121.45
100-95=5
5%=0.05
When the control variable is added, it influences the outcome. Adding control value increases the results.
References
Plonsky, L., & Oswald, F. L. (2017). Multiple regression as a flexible alternative to Hypothesis in L2 research. Studies in Second Language Acquisition, 39(3), 579-592.