# Recent questions in Analyzing categorical data

Analyzing categorical data

### How can you use two way-frequency tables to analyze data?

Analyzing categorical data

### The analysis of shafts for a compressor is summarized by conformance to specifications: roundnessconforms yes no surface finish yes 3455 conforms no 128 (a) If we know that a shaft conforms to roundness requirements, what is the probability that it conforms to surface finish requirements? (b) If we know that a shaft does not conform to roundness requirements, what is the probability that it conforms to surface finish requirements?

Analyzing categorical data

### The analysis of shafts for a compressor is summarized by conformance to specifications: roundnessconforms yes no surface finish yes 3455 conforms no 128 (a) If we know that a shaft conforms to roundness requirements, what is the probability that it conforms to surface finish requirements? (b) If we know that a shaft does not conform to roundness requirements, what is the probability that it conforms to surface finish requirements?

Analyzing categorical data

### For the poll described in the Chapter problem, assume that the respondents had been asked for their political party affiliation, and the responses were coded as 0 (for Democrat), 1 (for Republican), 2 (for Independent), or 3 (for any other response). If we calculate the average (mean) of the numbers and get 0.95, how can that value be interpreted?

Analyzing categorical data

### A palindromic number is a natural number whose reversal is identical to itself. For instance, the numbers: 1, 99, 101, 2112, 44444 are respectively palindromic numbers of 1, 2, 3, 4, and 5 digits. How many palindromic numbers between 1000 and 1000 000 are there?

Analyzing categorical data

### Is the mode the measure of central tendency that is best used with a skewed distribution?

Analyzing categorical data

### For each of the following variables, indicate whether they are categorical or numerical. Also, write down what type of graph can be drawn for each. a) Position of a university staff members. b) Weight of participants. C Air temperature on the Celsius scale D) The daily number of code lines written by a programmer

Analyzing categorical data

### Why is hair color classified as categorical data?

Analyzing categorical data

### Qualitative data that cannot be ranked is called categorical, nominal 1. True 2. False

Analyzing categorical data

### Which statement best characterizes the definitions of categorical and quantitative data? Quantitative data consist of numbers, whereas categorical data consist of names and labels that are not numeric. Quantitative data consist of numbers representing measurements or counts, whereas categorical data consist of names or labels Quantitative data consist of values that can be arranged in order, whereas categorical data consist of values that cannot be arranged in order. Quantitative data have an uncountable number of possible values, whereas categorical data have a countable number of possible values.

Analyzing categorical data

### Let g be an element of a group G. If $$|G|$$ is finite and even, show that $$g \neq 1$$ in G exists such that $$g^2 = 1$$

Analyzing categorical data

### The equation $$a=50h+50$$ represents the amount a that an air-conditioning repair company charges for h hours of labour. Make a table and sketch a graph of the equation

Analyzing categorical data

### Find the mean, median, mode, and range for each data set given. a. 7, 12, 1, 7, 6, 5, 11 b. 85, 105, 95, 90, 115 c. 10, 14, 16, 16, 8, 9, 11, 12, 3 d. 10, 8, 7, 5, 9, 10, 7 e. 45, 50, 40, 35, 75 f. 15, 11, 11, 16, 16, 9

Analyzing categorical data

### Tuddenham and Snyder obtained the following results for 66 California boys at ages 6 and 18 (the scatter diagram is football-shaped): average height at $$6 \approx 3$$ feet 10 inches, $$SD \approx 1.7$$ inches average height at $$18 \approx 5$$ feet 10 inches, $$SD \approx 2.5$$ inches, $$r \approx 0.80$$ a) Find the r.m.s. error for the regression prediction of height at 18 from height at 6. b) Find the r.m.s. error for the regression prediction of height at 6 from height at 18.

Analyzing categorical data

### For the chi-square tests in the analysis of categorical data, the rejection region 1.is always located in the lower tail of the distribution. 2.is always equally split in the two tails of the distribution. 3.is always located in the upper tail of the distribution. 4.depends on the probability of a type II error.

Analyzing categorical data

### Let N(x) be the statement “x has visited North India,” where the domain consists of the students in your section. Express each of these quantifications in English. $$\displaystyle{a}{)}∃{x}{N}{\left({x}\right)},{b}{)}∀{x}{N}{\left({x}\right)},{c}{)}¬∃{x}{N}{\left({x}\right)},{d}{)}∃{x}¬{N}{\left({x}\right)},{e}{)}¬∀{x}{N}{\left({x}\right)},{f}{)}∀{x}¬{N}{\left({x}\right)}$$

Analyzing categorical data

### Prove the following statement: if x is irrational and y is irrational then x+y is irrational

Analyzing categorical data

### All groups of order 14

Analyzing categorical data