What can you conclude from the univariate ANOVA results?
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1. What can you conclude from the univariate ANOVA results?
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- Give 2 examples of Mode in Measure of central tendency to ungrouped dataThe following cross-tabulation, based on GSS18SSDS-B data, examines the relationship between age (the independent variable) and presidential candidate one voted for in the 2016 U.S. presidential election (dependent variable). Notice we have recoded age into four categories: 18–29, 30–39, 40–49, and 50–59. Respondents of all other ages have been excluded from the analysis. Vote Clinton or Trump * RE_AGE Crosstabulation RE_AGE 18–29 30–39 40–49 50–59 Total Vote Clinton or Trump Clinton Count 65 96 77 78 316 % within RE_AGE 65.7% 61.1% 53.8% 45.6% 55.4% Trump Count 19 42 55 86 202 % within RE_AGE 19.2% 26.8% 38.5% 50.3% 35.4% Other candidate (specify) Count 12 17 10 5 44 % within RE_AGE 12.1% 10.8% 7.0% 2.9% 7.7% Didn’t vote for president Count 3 2 1 2 8 % within RE_AGE 3.0% 1.3% 0.7% 1.2% 1.4% Total Count 99 157 143 171 570…Using a sample of 500 adults with the following variables: genhelf - variable recording general self- reported health coded 1 = very good, 2 = good, 3 = fair, 4 = poor sbp - variable recording systolic blood pressure - age - age of the respondent in years sex coded 1 = male and 2 = female hi_sbp - indicator of high blood pressure coded 1 if the respondent's sbp is 130 or higher and 0 otherwise What type of chart is MOST appropriate for the variable sbp? a/ pie chart b/ bar chart c/ histogram
- State the null and alternative hypothesis for the dataWorking memory scores of those with anxiety are compared to working memory scores of those without anxiety. What is the appropriate experiment design for this scenario? factorial design between-participants design correlational design within-participants designWhat source of variation is found in an ANOVA summary table for a within subjects design that is not in an ANOVA summary table for a between subjects design. What happens to this source of variation in a between-subjects design?
- account_circle Math StatisticsQ&A LibraryPolokwane Butchery supplies Vienna sausages in the entire of KZN province. An Inspector from the CCSA has been sceptical of the mass of the Vienna sausage packs after receiving numerous complaints. He wants to investigate the marked mass shown on Vienna sausages. A pilot study showed a mean of 11.8kg per pack and a variance of 0.49kg. How many packs should the Inspector sample in order to be 99% confident that the sample mean will differ by at most 0.2kg? Polokwane Butchery supplies Vienna sausages in the entire of KZN province. An Inspector from the CCSA has been sceptical of the mass of the Vienna sausage packs after receiving numerous complaints. He wants to investigate the marked mass shown on Vienna sausages. A pilot study showed a mean of 11.8kg per pack and a variance of 0.49kg. How many packs should the Inspector sample in order to be 99% confident that the sample mean will differ by at most 0.2kg?…If a two-factor analysis of variance produces a statistically significant interaction, then what can you conclude about the interaction? either the main effect for factor A or the main effect for factor B is also significant both the main effect for factor A and the main effect for factor B are significant neither the main effect for factor A nor the main effect for factor B is significant the significance of the main effects is not related to the significance of the interactionWhat variables do Teczar find to have the most significant controlled association with women in ministries?
- Are the samples dependent or independent?The following figure shows the results from a study linking BMI to pasta intake by weight categories (colors). Based on this graph, what would your conclusion be? 08 60 Body Mass Index (kg/m2) 40 20 0 1000 2000 Pasta Intake, kcal/dayLook at the MS Excel file (titled “Easy_Tough”) available in the Blackboard. This file carries data about average MathSAT scores of 297 colleges and universities located in the USA and they are all classified into two groups of colleges and universities. One group of institutions are tough to graduate for students and another group of institutions are easy to graduate for students. Using MS Excel, perform analysis of variance test to examine whether the mean MathSAT score between these two groups are same or not. this is the data on excel Easy to graduate colleges Tough to graduate colleges 547 495 550 526 451 480 470 533 617 429 554 529 524 568 620 550 650 535 519 506 486 540 494 509 513 459 615 526 524 377 525 543 608 490 537 513 550 466 520 544 540 502 497 480 520 531 533 470 455 400 525 494 603 395 578 445 459 460 525 372 575 504 564 480 509 520 530 542 670 522 590 440 590 510 532 419 585 330 514…