Important Stats on US Immigration and Enforcement

Immigration and enforcement in the US are complex topics, but some numbers tell a compelling story. The US has a long history of immigration, with over 12 million immigrants arriving in the country between 1820 and 1910.

Many immigrants come to the US seeking better economic opportunities. In 2019, the top countries of origin for immigrants in the US were Mexico, China, Cuba, Dominican Republic, and India.

The US immigration system is often described as a "broken" system, but some numbers suggest it's more nuanced. The US Citizenship and Immigration Services (USCIS) received over 1.3 million applications for green cards in 2019.

The US has a significant undocumented immigrant population. In 2019, it's estimated that approximately 10.5 million undocumented immigrants lived in the US.

Border Encounters are a critical aspect of immigration data, and the US Customs and Border Protection (CBP) provides various statistics on this topic.

The Nationwide Encounters page breaks down data into three categories: USBP Title 8 apprehensions, OFO Title 8 inadmissibles, and Title 42 expulsions. These statistics are available for fiscal years 2020 and 2021 to date.

The Southwest Land Border Encounters page specifically focuses on data from the southwest land border, including apprehensions, inadmissible subjects, and expulsions. This data is crucial for understanding the flow of migrants across this border.

Data is available for the Northern Land Border, Southwest Land Border, and Nationwide encounters, providing a comprehensive view of immigration trends. This data is essential for policymakers and researchers to make informed decisions.

The Southwest Land Border Encounters page also breaks down data by USBP Sector and OFO field office, offering a more detailed analysis of immigration patterns. This level of detail is valuable for identifying areas of high activity and developing targeted strategies.

Border enforcement is a complex task, and the numbers can be staggering. CBP's Border Enforcement Statistics page provides a wealth of information on apprehensions, findings of inadmissibility, recidivism, and arrests of criminal noncitizens at the border.

The law enforcement component within CBP, known as OFO, plays a crucial role in carrying out the agency's mission at all ports of entry. This includes facilitating lawful international travel.

CBP's statistics show that apprehensions can be a significant concern at the border. In fact, the agency's data on apprehensions is a key part of their Border Enforcement Statistics page.

OFO's work at ports of entry is vital to ensuring the safety and security of travelers.

Statistics is a branch of applied mathematics that uses mathematical tools to analyze data and make informed decisions.

A variable is a data set that can be counted and marks a characteristic or attribute of an item, such as the make, model, year, mileage, color, or condition of a car.

There are two main types of variables: qualitative and quantitative. Qualitative variables are specific attributes that are often non-numeric, while quantitative variables are studied numerically and have weight when they’re about a non-numerical descriptor.

Descriptive statistics describe the properties of sample and population data, including mean, median, mode, range, variance, and standard deviation.

The average total compensation for a statistician with one to three years of experience was $81,885 as of December 2023, increasing to $109,288 with 15 years of experience.

Here are the two main areas of statistics: TypeDescriptionDescriptiveDescribes the properties of sample and population dataInferentialUses those properties to test hypotheses and draw conclusions

Nationwide Encounters provide USBP Title 8 apprehensions, OFO Title 8 inadmissibles, and Title 42 expulsions for fiscal years 2020 and 2021 to date.

Data is available for encounters at the Northern Land Border, Southwest Land Border, and Nationwide, which includes air, land, and sea modes of transportation.

The Nationwide Encounters page offers a comprehensive view of encounters across the country, making it easier to track and analyze trends.

Nationwide Encounters data is available for fiscal years 2020 and 2021 to date, giving us a clear picture of recent trends and patterns.

Custody and Transfer statistics offer valuable insights into the operations of CBP custody.

Data on in-custody information is tracked by location, providing a detailed picture of who is in custody and where they are being held.

CBP custody metrics also include dispositions for inadmissible and apprehended populations, helping to identify trends and patterns in these cases.

Transfer destinations for populations leaving CBP custody are also monitored, allowing for a better understanding of where individuals are being sent after being released from custody.

The Migrant Protection Protocols, also known as MPP, is a program that provides data on migrant enrollment, referrals to U.S. Citizenship and Immigration Services, and outcomes of MPP cases.

Enrollment in the MPP program has been tracked, showing a significant number of migrants participating in the program.

Referrals to U.S. Citizenship and Immigration Services have been made through the MPP program, allowing migrants to pursue their immigration options.

Data from the Executive Office of Immigration Review shows that MPP cases have resulted in a notable number of outcomes, providing insight into the program's effectiveness.

These outcomes include, but are not limited to, removal orders and other immigration decisions.

Statistics is a powerful tool for understanding data, and it all starts with variables. A variable is a data set that can be counted and marks a characteristic or attribute of an item. For example, a car can have variables such as make, model, year, mileage, color, or condition.

There are two main types of variables: qualitative and quantitative. Qualitative variables are specific attributes that are often non-numeric, such as gender, eye color, or city of birth. Quantitative variables, on the other hand, are studied numerically and only have weight when they’re about a non-numerical descriptor, such as the mileage driven.

Quantitative variables can be further broken into two categories: discrete and continuous. Discrete variables have limitations in statistics and infer that there are gaps between potential discrete variable values, such as the number of points scored in a football game. Continuous variables, on the other hand, run along a scale and can be measured into decimals, such as the height of football players.

Statisticians use variables to collect and analyze data, and their work can be divided into two main areas: descriptive statistics and inferential statistics. Descriptive statistics describe the properties of sample and population data, while inferential statistics use those properties to test hypotheses and draw conclusions.

Here's a summary of the two main types of variables:

Qualitative variables are often used to determine what percentage of an outcome occurs for any given qualitative variable, while quantitative variables are used to study the strength and nature of the relationship between variables.

In statistics, variables are the building blocks of data analysis, and understanding them is essential for making informed decisions. By recognizing the different types of variables and how they can be used, you can unlock the power of statistics and gain valuable insights from your data.

The Border Rescues and Mortality Data page provides a wealth of information on CBP rescues and fatalities.

CBP rescues data is available on this page, offering insights into the number of people rescued by Customs and Border Protection.

The Office of Professional Responsibility’s CBP-Related Deaths data is also included, providing a detailed look at border-related fatalities.

This data is crucial for understanding the scope of the issue and informing policy decisions.

The U.S. Border Patrol’s Missing Migrant Program data is another valuable resource, shedding light on the number of people who go missing while attempting to cross the border.

Phone support is still a top choice for consumers, with over 76% of all consumers preferring it to reach customer support representatives. This is according to a study by the CFI Group.

More than 50% of customers across all age groups typically use the phone to reach out to a service team. This makes phone support the most-used channel for customer service.

Interestingly, while 63% of customer service teams use text messaging, only 78% of customers use text messaging for communicating with a company. This shows that while teams are trying to adapt, they still have a way to go in meeting customer preferences.

Here are some key statistics on phone support:

Consumers prefer to resolve issues independently, but many companies are failing to provide them with the necessary tools. 69% of consumers first try to resolve their issue on their own, but less than one-third of companies offer self-service options.

Customers are looking for information that's easy to find, but often they're frustrated by the lack of it. 28% of consumers say the most frustrating issue is information that is simple but hard to find.

Knowledge bases are the preferred self-service channel, but many companies are not using them. Customers prefer knowledge bases over all other self-service channels.

Here are some key statistics on self-service options:

Social media has become a crucial platform for businesses to connect with customers. 79% of American internet users are on Facebook, making it the most popular social media platform.

Many young adults, especially those between 18-34, are likely to follow a brand through social media channels. 95% of them are interested in doing so.

To tap into this potential, consider providing customer service via social media channels. Think about all the people your brand could connect with if you make the switch.

When you're working with statistics, you can't always gather data from every single data point in a population. This is where sampling techniques come in, allowing you to create a representative subset of the population that's easier to analyze.

Statistics relies on sampling techniques to gather information because it's often not possible to gather data from every data point. This is why sampling techniques are so important in statistics.

There are several primary types of sampling, including those that allow you to create a representative subset of the population. This is crucial for gathering accurate information.

Inferential statistics is a tool that helps us draw conclusions about a population based on a sample of data. It's like trying to estimate the average demand for a product by surveying a small group of consumers.

Inferential statistics is used to make generalizations about large groups, such as predicting future events or projecting the return of a security. This is because it allows us to calculate the probability that our sample data accurately represents the population.

Regression analysis is a widely used technique of statistical inference that helps us determine the strength and nature of the relationship between variables. It's used to analyze the output of a regression model for statistical significance.

Statistical significance suggests that a result is not likely to have occurred randomly or by chance, and is often used in academic disciplines and research. Having statistical significance is crucial for drawing reliable conclusions from data.

Inferential statistics employs techniques like correlation and regression analysis to relate variables in a data set. This can be used to estimate forecasts or infer causality, helping us better understand the relationships between different variables.

Statistics relies on sampling techniques to gather a representative subset of the population that's easier to analyze.

There are several primary types of sampling, including simple random sampling, systematic sampling, and stratified sampling.

Simple random sampling gives every member of the population an equal chance of being selected for analysis. For example, 100 individuals lined up and 10 chosen at random.

Systematic sampling is similar, but it uses a random starting point and selects individuals at a specified regular interval. If 100 individuals are lined up and numbered, and the random starting point is the seventh individual, every subsequent ninth individual is selected.

Stratified sampling divides the population into subgroups based on similar characteristics, and then takes a sample from each subgroup in proportion to how representative that subgroup is of the population.

Inferential statistics is used to draw conclusions about the characteristics of a population from a sample. It's also used to determine how certain you can be of the reliability of those conclusions.

Regression analysis is a widely used technique of statistical inference that determines the strength and nature of the relationship between a dependent variable and one or more explanatory variables.

CBP Discipline and Safety is a crucial aspect of the agency's operations. In FY 2019, the CBP Discipline Overview provided a comprehensive statistical analysis of disciplinary actions taken against CBP employees.

A total of 6 specific sections were addressed in the report, each providing valuable insights into the agency's disciplinary actions. These sections included Disciplinary Breakdown by Program Office, CBP Information Center, Employee Arrests, Drug-Free Workplace, Use of Force Allegations, and Mandatory Removals of Law Enforcement Officers.

The report highlighted the importance of maintaining a safe and disciplined work environment. In FY 2019, CBP employees were subject to disciplinary actions, including mandatory removals of law enforcement officers.

Here are some key statistics from the report:

It's worth noting that the exact numbers of occurrences for each disciplinary action are not specified in the report.

I'm excited to share with you the importance of public data and resources.

The CBP Public Data Portal is a treasure trove of downloadable data sets, making it easy to access and explore.

Public data is more than just numbers and statistics; it can be a powerful tool for understanding trends and patterns.

You can visit the CBP Public Data Portal to get started and explore the various data sets available.

Statistics is a fascinating field that's all around us, from business to medicine to government. It's the study and manipulation of data, including ways to gather, review, analyze, and draw conclusions from data.

Statistics is used in virtually all scientific disciplines, from the physical and social sciences to business, medicine, the humanities, government, and manufacturing. It's fundamentally a branch of applied mathematics that developed from the application of mathematical tools, including calculus and linear algebra, to probability theory.

There are two major areas of statistics: descriptive and inferential statistics. Descriptive statistics involve summarizing and describing the basic features of data, while inferential statistics involve making conclusions or predictions about a larger population based on a sample of data.

Statistics can be communicated at different levels, ranging from non-numerical descriptors (nominal-level) to numerical references to a zero-point (ratio-level). This means that statistics can be expressed in different ways, depending on the type of data and the level of precision needed.

Some common sampling techniques used to compile statistical data include simple random, systematic, stratified, or cluster sampling. These techniques help ensure that the sample is representative of the larger population.

Here are some key statistics-related terms to keep in mind:

As a statistician, you can hold various titles and positions within a company. The average total compensation for a statistician with one to three years of experience was $81,885 as of December 2023, increasing to $109,288 with 15 years of experience.

Customer service is a crucial aspect of any business, and understanding consumer behavior is essential to providing an excellent experience. It takes 12 positive customer experiences to make up for one negative experience, which highlights the importance of getting it right.

Consumers are more likely to share their experiences with others, whether good or bad. In fact, 36% of consumers will share their customer service experience, with many reporting posting on social media platforms like Facebook and Instagram. This shows just how powerful word-of-mouth can be.

A single bad experience can have a significant impact on a customer's decision to leave a business. 65% of customers have changed to a different brand because of a poor experience, while 67% of customers report a terrible customer experience as the reason for switching businesses.

Here are some key statistics to keep in mind:

By prioritizing customer service and understanding consumer behavior, businesses can set themselves up for success and build a loyal customer base.

Understanding consumer behavior is key to providing excellent customer service. It takes 12 positive customer experiences to make up for one negative experience.

Consumers are more likely to share their experiences with others, whether good or bad. 36% of consumers will share their customer service experience, whether good or bad, and more than one-third report posting on Facebook, followed closely by Instagram.

Customer behavior is influenced by their past experiences, and a single negative experience can lead to a loss of business. 65% of customers said they have changed to a different brand because of a poor experience.

The impact of customer service is far-reaching, affecting not only the customer but also the company's reputation. 94% of American customers will recommend a company whose service they rate as “very good.”

To provide excellent customer service, it's essential to understand what customers value most. 72% of customers will share their good experiences with others, and 72% will tell six or more people if they have a satisfying experience.

Here are some key statistics to keep in mind:

By understanding consumer behavior, you can tailor your customer service approach to meet their needs and expectations. This will help you provide a positive experience that will keep customers coming back.

Choosing the right support channels is crucial for providing excellent customer service. With so many options available, it can be overwhelming to decide which ones to use.

Phone and email have been the traditional channels of customer service since the 1960s, when call banks first emerged.

Each channel has its pros and cons. Live chat, for instance, provides an instant response, but may not be suitable for complex issues.

Co-browsing and virtual video calls allow for a more personal interaction, but may require additional equipment.

Social media mentions are becoming increasingly popular, but may not be suitable for sensitive or confidential issues.

The frequency of use for each channel varies, but phone and email are still the most commonly used by support teams and customers.

Team management and performance are crucial for delivering excellent customer service. 88% of high-performing service decision-makers are investing significantly in agent training compared to only 57% of underperformers.

Having a well-trained team can make all the difference in customer satisfaction. 83% of high-performing service agents say they get the training they need to do their job well compared to only 52% of underperformers.

It's not just about training, but also about empowering your team with the right tools. 69% of high-performing service agents actively look for situations to use artificial intelligence (AI) compared to only 39% of underperformers.

Here's a comparison of high-performing and underperforming service teams:

These statistics show that investing in your team's training and providing them with the right tools can lead to better performance and customer satisfaction.