Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.

An educational scientist wants to examine the correlation between years of education and job satisfaction. To address this question, the scientist recruits a group of participants and has each complete a self-administered survey; the first question asks how many years of education the participant has (e.g., 12 = high school diploma, 14 = associate’s degree, 16 = bachelor’s degree, 18 = master’s degree). The remaining questions consist of the Acme Job Satisfaction Index (AJSI), which produces a score between 0 and 60 (0 = very unsatisfied with job, 60 = very satisfied with job).

Data set: Ch 08 – Exercise 05A.sav Codebook Variable: yearsed Definition: Number of years of education Type: Continuous Variable: ajsi Definition: Acme Job Satisfaction Index score Type: Continuous (0 = very unsatisfied with job, 60 = very satisfied with job)

1. Write the hypotheses.

2. Run the criteria of the pretest checklist (normality [for both variables], linearity, homoscedasticity) and discuss your findings.

3. Run the bivariate correlation, scatterplot with regression line, and descriptive statistics for both variables and document your findings (r and Sig. [p value], ns, means, standard deviations) and hypothesis resolution.

4. Write an abstract up to 200 words detailing a summary of the study, the bivariate correlation, hypothesis resolution, and implications of your findings

find the cost of your paper

Write the integral expression for the two-parameter output correlation function  over the time intervals .

Consider the following mean-square differential equation, driven by a WSS random process  with psd The differential equation is subject to the initial condition , where the random variable  has zero-mean, variance 5, and….

Repeat the corresponding segment of the correlation function periodically.

If a stationary random process is periodic, then we can represent it by a Fourier series with orthogonal coefficients. This is not true in general when the random process, though….

Show that an m.s. derivative process  exists here.

Certain continuous time communications channel can be modeled as signal plus an independent additive noise (a) The receiver must process  for the purpose of determining the value of the message random….