Why are my p-value and test statistic values wrong?

String getPhone() { return phone; } public void setPhone(String phone) { this.phone = phone; } public String getRoles() { return roles; } public void setRoles(String roles) { this.roles = roles; } public String getGender() { return gender; } public void setGender(String gender) { this.gender = gender; } public String getCountry() { return country; } public void setCountry(String country) { this.country = country; } public String getState() { return state; } public void setState(String state) { this.state = state; } public String getCity() {
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package com.example.demo.model;import javax.persistence.Column;import javax.persistence.Entity;import javax.persistence.GeneratedValue;import javax.persistence.GenerationType;import javax.persistence.Id;import javax.persistence.Table;@Entity@Table(name = "user")public class User { @id @GeneratedValue(strategy = GenerationType.IDENTITY) private int id; @Column(name = "username") private String username; @Column(name = "password") private String password; @Column(name = "email") private String email; @Column(name = "address") private String address; @Column(name = "phone") private String phone; @Column(name = "roles") private String roles; @Column(name = "gender") private String gender; @Column(name = "country") private String country; @Column(name = "state") private String state; @Column(name = "city") private String city; public int getId() { return id; } public void setId(int id) { this.id = id; } public String getUsername() { return username; } public void setUsername(String username) { this.username = username; } public String getPassword() { return password; } public void setPassword(String password) { this.password = password; } public String getEmail() { return email; } public void setEmail(String email) { this.email = email; } public String getAddress() { return address; } public void setAddress(String address) { this
 

Related to Why are my p-value and test statistic values wrong?

1. Why is my p-value not significant?

There could be several reasons for a non-significant p-value. It could be due to a small sample size, low effect size, or high variability in the data. It is also possible that the null hypothesis is true and there is no significant difference between the groups being compared.

2. Why is my test statistic value different from what I expected?

The test statistic value is calculated based on the data and the chosen statistical test. If the data is entered incorrectly or if a different test is used, the test statistic value will be different from what was expected. It is important to double-check the data and the chosen test to ensure accurate results.

3. Can a p-value be negative?

No, a p-value cannot be negative. It represents the probability of obtaining the observed results or more extreme results if the null hypothesis is true. Since probability cannot be negative, a p-value will always be between 0 and 1.

4. Why is my p-value different from someone else's?

P-values can vary depending on the sample size, effect size, and variability in the data. It is also possible that different statistical tests were used, resulting in different p-values. It is important to understand the context and methodology of the study to compare p-values accurately.

5. Can I rely solely on p-values to make a conclusion?

No, p-values should not be the only factor considered when making a conclusion. It is important to also consider the effect size, confidence interval, and other relevant factors in interpreting the results of a statistical test. Additionally, p-values only provide evidence against the null hypothesis and do not prove causation.

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